Staff Software Engineer - Forward Deployed
About the job
- At least 8 years of software engineering experience, including significant experience building data, machine-learning, or backend systems.
- Deep proficiency in Python and hands-on experience with Hugging Face, LangChain, OpenAI, Pinecone, large language models, AI agents, and related ecosystems.
- Experience with full-stack and API-based deployment patterns, Docker, FastAPI, Kubernetes, and cloud environments such as GCP, AWS, or Azure.
- Experience with workflow orchestration libraries, pub/sub systems such as Kafka, and schema governance.
- Expertise in data governance and operations, including Unity Catalog and policy management, cluster and job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes.
- For teams with an applied AI/ML focus, experience with MLOps frameworks and practices, including model versioning, monitoring, lifecycle management, and scalable ML systems such as RAG pipelines.
- Strong product and system design instincts, including translating business needs into technical architecture.
- Experience building usable systems from messy data and ambiguous requirements.
- Experience owning projects from scoping through deployment in ambiguous, high-stakes environments.
- Willingness to be on-call for customers when situations arise.
- Willingness to travel for on-site client engagements as needed.
- Availability to work from the office a few days per week, depending on team needs; some NYC-based teams require three days per week on-site.
- Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI-driven solutions, including LLM and agentic systems.
- Identify transformational opportunities in messy, ambiguous workflows and turn them into repeatable systems.
- Lead architecture design and trade-off discussions across performance, scalability, cost, and reliability, including for RAG pipelines and production-grade AI applications.
- Own projects from the first discovery call through full deployment, including client-facing delivery, internal coordination, and post-launch iteration.
- Build shared infrastructure, reusable components, and internal playbooks to improve the team, including MLOps practices for model versioning, monitoring, and lifecycle management.
- Coach and mentor mid-level engineers and help shape the culture of forward-deployed AI engineering.
About Invisible
Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most.
Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere.
Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets.
Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology.
About The Role
As a Staff Forward Deployed Engineer (FDE) at Invisible, you'll lead high-impact, AI-powered solutions that reshape how our clients operate their most critical workflows. You won't just build and deploy — you'll drive the strategy, architecture, and execution of end-to-end systems, working directly with clients.
This is a hybrid role: equal parts AI engineer, software builder, and technical consultant. It's perfect for someone who wants to be hands-on with models and close to the impact they generate. The team is increasingly focused on applied AI work — building and deploying LLM-powered and agentic systems in production — so strong ML engineering instincts can be a valuable addition alongside your architecture and leadership experience.
What You’ll Do
- Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI-driven solutions, including LLM and agentic systems
- Identify transformational opportunities in messy, ambiguous workflows and turn them into repeatable systems
- Lead architecture design and trade-off discussions across performance, scalability, cost, and reliability — including for ML/AI-specific systems like RAG pipelines and production-grade AI applications
- Own projects from first discovery call through full deployment — including client-facing delivery, internal coordination, and post-launch iteration
- Build shared infrastructure, reusable components, and internal playbooks to level-up the team, including MLOps practices for model versioning, monitoring, and lifecycle management
- Coach and mentor mid-level engineers and help shape the culture of forward-deployed AI engineering at Invisible
What We Need
- 8+ years of software engineering experience, including significant time spent building data, ML, or backend systems
- Python & ML/LLM Frameworks: Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems, including LLMs and AI Agents
- Deployment & Infrastructure: Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS, Azure)
- Platform Orchestration: Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance
- Data Management: Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes
- ML Operations (for teams with an applied AI/ML focus): Experience with MLOps frameworks and best practices — model versioning, monitoring, and lifecycle management — and designing scalable ML systems such as RAG pipelines
- Strong product and system design instincts — you understand business needs and how to translate them into technical architecture
- Experience building usable systems from messy data and ambiguous requirements
- Excellent communication and client-facing skills; you've led conversations with technical and non-technical stakeholders alike
- Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments
- Be willing to be on-call for our customers when situations arise
- Travel: Willingness to travel for on-site client engagements as needed
- Onsite: Available to work from the office a few days per week, depending on team needs — some NYC-based teams require 3 days per week onsite; your specific requirement will depend on the team you're placed with
What’s In It For You
Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity.
The annual salary range for this position, depending on level, is: $210,000 - $300,000 USD
You can find more information about our geographic pay tiers here. During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living.
*Bonuses and equity are included in all full-time offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process.
What It's Like to Work at Invisible:
At Invisible, we’re not just redefining work—we’re reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI.
We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We’re not for everyone, and we’re okay with that. If you’re looking for predictable routines, this isn’t the place for you. But if you’re driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you’ll fit right in.
Country Hiring Guidelines:
Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process.
AI Interviewing Guidelines:
Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. Click here to learn more about how we use AI and our guidelines for candidates.
Accessibility Statement:
We are committed to providing reasonable accommodations for individuals with disabilities. If you require an accommodation to participate in the application or interview process, please submit your request using our accommodation request form. A member of our team will follow up to support your request. Here is the link the google form: https://docs.google.com/forms/d/e/1FAIpQLScqsu0PCQ0m0lwt-VFeXovNbZxWk0jogv8QI_ciGqZsIbSBjQ/viewform?usp=sharing&ouid=102356854798492362557
Equal Opportunity Statement:
We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law.
Due to a high volume of candidates, Invisible may use automated decision-maker technologies to filter candidates based on response to our application questions and other provided information. Our use of automated decision-making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria. If you object to our use of automated decision-making please contact us.
About the company
Invisible Technologies combines AI with a global workforce to automate repetitive digital work under a subscription-based model with a dedicated assistant for each client. Clients choose a plan and tasks are automatically routed to AI or human agents, with a transparent portal that shows progress, usage, and billing. The service emphasizes a high-touch, long-term partnership and a predictable, managed workflow, differentiating from traditional outsourcing and big automation providers with its dedicated assistant and visibility. The goal is to streamline operations, boost efficiency, and cut costs by delivering faster, more transparent digital work at scale.
Company Size
1,001-5,000
Company Stage
Growth Equity (Venture Capital)
Total Funding
$107.9M
Headquarters
New York City, New York
Founded
2015
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Simplify's Take
What believers are saying
- Invisible raised $100 million in September 2025 at over $2 billion valuation.
- March 2026 WeCP acquisition strengthens high-precision AI training and expert validation.
- Matt Fitzpatrick said July 2026 humans stay essential for AI training for decades.
What critics are saying
- Scale AI, Surge AI, and Mercor outspend Invisible in specialist talent acquisition.
- Contractors report abrupt project endings, weak communication, and inconsistent workload across projects.
- If labs internalize human feedback or synthetic data wins, Invisible loses core demand.
What makes Invisible Technologies unique
- Invisible combines AI training, human expertise, and enterprise workflow automation end-to-end.
- Meridial plus WeCP adds expert assessment, RL gyms, and simulation depth.
- Its client list includes Microsoft, AWS, Cohere, SAIC, and Charlotte Hornets.
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Benefits
- Remote Work Options
- Performance Bonus
- Company Equity
Growth & Insights and Company News
6 month growth
2%1 year growth
8%2 year growth
6%An interview with Scott Downes, founder & CEO of Supernal AI. S SuperbCrew is a trusted resource for discovering innovative companies, emerging startups, and the latest technology trends. Scott Downes is CEO and founder of Supernal.ai. He is a seasoned technology executive with deep expertise in scaling AI-powered operations. As former CTO of Invisible Technologies - ranked #3 on the Inc. 5000 fastest-growing AI companies - he led the team and platform that brought the company to global scale and $134M in revenue. He also served as CTO at Infinity Constellation, the world's premier incubator for AI-enabled services. At Supernal, Scott is on a mission to bring the transformative power of modern AI to small and medium-sized businesses. Q: Could you provide its readers with a brief introduction to your company? A: Supernal AI helps small and mid-market businesses put advanced AI to work in ways that are practical, useful and tied to real business outcomes. I started Supernal after working at Invisible Technologies, where I had a front-row view of the development of the frontier models that helped ignite the current AI revolution. I wanted to take that same level of technology and make it accessible to businesses that are often overlooked. Today, SuperbCrew build AI operating systems and AI employees that help companies scale without losing the vision, culture and ways of working that made them successful in the first place. Q: What makes you the best choice? How are you unique? A: For years, businesses have paid what I think of as a double tax. They pay for software, and then they pay for people to operate software they may not fully use or even like. SuperbCrew want to change that model. Supernal combines a strong technology platform with a services approach that is deeply hands-on. Many people on its team worked at companies involved in building the frontier models powering the AI revolution, but SuperbCrew do not simply hand clients a platform and tell them to figure it out. SuperbCrew work backward from the business outcome they are trying to achieve and build around that. The goal is for technology to serve the business, not for the business to reorganize itself around technology. Q: Any highlights about your latest announcement? A: Its work on The Thorne Protocol has been an especially meaningful proof point. Creative industries are at the center of the debate over whether AI will replace the most human parts of work. SuperbCrew wanted to demonstrate another model. The story was written by humans, the performances were human and the production used real cameras, while AI supported the process around the creative team. The point was not simply to make a film trailer. It was to show that AI can accelerate complex work without taking the creative decisions away from people. SuperbCrew sometimes describe it as giving people an Iron Man suit: the technology should increase what talented people are capable of doing, not replace the person inside the suit. Q: What can SuperbCrew expect from you in the next 6 months? What are your plans? A: SuperbCrew is continuing to expand the idea of AI employees operating on top of AI operating systems built around the way a business actually works. The Thorne Protocol is a very visible example because filmmaking is complex, expensive and deeply human, but it is not a pivot into becoming a film technology company. The same approach applies to financial services and other industries where skilled people are trying to scale complicated processes. Over the next six months, SuperbCrew expect to keep proving that companies can use AI to create greater impact and scale while keeping humans in control of the work that matters most. Q: What is the best thing about your company that people might not know about? A: The thing people may not realize is how intentionally SuperbCrew combine elite AI talent with an almost fanatical focus on service. Many technology companies build a platform and leave the customer to figure out how to make it useful. Services firms may understand the customer's problem but lack the underlying technology. SuperbCrew built Supernal to do both. Its team brings experience from companies involved in building the frontier models behind today's AI boom, but its job is not finished when the technology works. It is finished when it creates an outcome the customer actually cares about.
Leading generative AI companies building advanced RAG solutions in 2026. DataRobot AI, Algoworks, BeyondKey, and Invisible Technologies are among the companies working on RAG-based AI solutions in 2026. They help businesses build smarter AI tools that can search for information and provide useful answers. Published on: 11 Jun 2026, 11:45 am Updated on: 11 Jun 2026, 11:45 am Overview. * DataRobot AI helps businesses build AI tools and use data more effectively. * Algoworks builds custom AI solutions that help companies bring automation into daily work. * BeyondKey creates AI-powered tools that help businesses find and manage information faster. Artificial intelligence has completely changed the business world. Companies are now using AI tools for customer support, data work, internal tasks, and many other daily operations. However, basic AI systems have multiple limitations. They may not always have the latest or most relevant information. This is where RAG solutions step in. Discover more AI technology insights Industry news analysis Crypto market trends Retrieval-Augmented Generation (RAG) allows AI tools to retrieve information from selected sources before generating an answer for users. These systems help businesses to create an AI system that is more useful for their own needs. The use of RAG solutions allows organizations to build smarter search tools, virtual assistants, and workplace apps. Some focus on customer experience, while others use AI to improve employee work. If you are looking for companies working on advanced generative AI and RAG solutions, these are a few names worth considering. DataRobot AI. Location: USA, Boston Founded in: 2012 DataRobot AI helps businesses build AI solutions without overcomplicating the process. The company develops tools that help teams use data, build AI models, and improve everyday decision-making. DataRobot AI is particularly useful for organizations that want an easier-to-use AI solution and don't need a large team to operate it. Its solutions help companies bring AI into their existing work without major changes. Algoworks. Discover more Currencies & Foreign Exchange Machine Learning & Artificial Intelligence Data analytics tools Location: Ramsey, New Jersey Founded in: 2006 Algoworks designs software, offers cloud services, and provides AI solutions. The company helps businesses build custom AI applications that fit their needs. Its RAG solutions enable companies to link AI tools to their own data. Algoworks is highly recommended for developing AI systems that fit the business workflow and not the other way around. Xperiencify Labs. Location: Austin, Texas, USA Founded in: 2019 Xperiencify Labs is working on AI-based solutions to improve digital experiences. The company develops tools to improve users' interaction with technology. This platform is specifically recommended for businesses looking for AI solutions focused on improving user experience. Its approach helps companies create tools that are easier to use. Codete. Location: Kraków, Poland Founded in: 2010 Codete is a software development company providing modern technology solutions. The company helps businesses embed AI features into their applications. Codete is recommended primarily for its ability to combine software skills with AI development. Companies can use the support to make existing apps smarter and provide users with better access to information. BeyondKey. Location: Chicago, Illinois Founded in: 2005 BeyondKey designs AI solutions to help businesses manage information and daily activities. The company is focused on generative AI and business applications. This company offers a practical solution for complex business problems. These are solutions companies can leverage to find information faster and make work easier for teams. Invisible Technologies. Location: San Francisco, California Founded in: 2015 Invisible Technologies helps companies implement technology and automation more effectively. The firm is developing AI tools for different business processes. Its focus on practical use cases is the primary reason why businesses should consider it. With the solution the company provides, organizations can reduce repetitive work and improve how teams handle daily tasks. Why RAG solutions are growing fast. Companies today process enormous amounts of information daily. It can be hard to find the right details fast. That's one of the main reasons companies are moving to RAG solutions. These AI systems allow companies to query their own data for answers. This makes them useful for customer support, employee help desks, and internal search. Another reason for their growth is trust. Companies want AI tools that respond to questions using their own data. RAG reduces errors based on the data sources you select. With AI becoming a bigger part of the workplace, companies are going to be looking for tools that are easy, reliable and helpful. RAG is changing how businesses use AI. Generative AI is no longer simply chatbots. Companies are now looking for AI tools that can understand their data and help them solve their daily problems. Businesses are moving toward smarter AI solutions with the help of companies like DataRobot AI, Algoworks, BeyondKey and Invisible Technologies. Each company focuses differently, ranging from automation to custom AI development. There isn't one AI company that is best for everyone. Some businesses just want better search tools. Others want AI to help them run their day-to-day. What the company wants to do will influence the right choice. As AI grows, businesses are likely to use more RAG solutions to manage information. FAQs. What is RAG in generative AI? Ans: RAG helps AI tools find information from selected sources before answering questions. It makes responses more useful by enabling AI to work with up-to-date, specific information. Why are companies using RAG solutions? Ans: Companies use RAG solutions to manage information better, improve AI responses, and help employees or customers find answers faster without spending extra time searching manually. Which companies provide RAG solutions? Ans: DataRobot AI, Algoworks, BeyondKey, and other AI companies provide solutions that help businesses create AI tools connected to their own information. Can small businesses use RAG-based AI tools? Ans: Yes, small businesses can use RAG tools for customer support, document searches, and simple automation tasks to save time and improve daily work. Is generative AI useful for businesses? Ans: Yes, generative AI helps businesses improve productivity, automate regular tasks, and create better digital experiences for customers and employees.
Invisible Technologies agrees to acquire WeCP to strengthen expert validation for high-precision AI workflows. Business wire India. Invisible Technologies today announced it has entered into an agreement to acquire WeCP, an AI-native technical assessment and intelligence platform known for its rigorously validated evaluation frameworks. As AI systems are deployed across engineering, healthcare, finance, and other complex domains, the quality of the experts shaping those systems has become increasingly critical. High-stakes AI workflows require structured, high-fidelity validation of domain specialists at scale. WeCP brings an AI-native assessment and intelligence platform, which to date has created over two million real-world technical interviews and more than 18,000 targeted domain and role-specific assessment frameworks across engineering, banking, healthcare, finance, and advanced STEM domains. It also has enhanced infrastructure for RL gyms and task simulation. Built over five years of continuous iteration, the platform enables precise evaluation of advanced technical talent. "This acquisition expands our foundation of high-precision AI training," said Matt Fitzpatrick, CEO of Invisible Technologies. "The performance of advanced AI systems depends on trusted human expertise, and WeCP's assessment engine has built one of the most extensively refined technical assessment libraries in the market. By integrating WeCP into Invisible's AI training platform, Meridial, we're raising the bar on precision and speed for expert evaluation across our platform while also accelerating our capabilities in RL gyms and simulated environments." WeCP was founded by NIT Trichy alumni Abhishek Kaushik, formerly of Google, and Mohit Goyal, formerly of Meta, with a vision to modernize technical evaluation. What started as an effort to improve interview question generation evolved into a comprehensive system for measuring real-world skill, reasoning, and domain expertise. Kaushik and Goyal will join Invisible along with several key members of the WeCP team and continue working on their core mission to advance expert assessment infrastructure. "We built WeCP to solve a fundamental challenge: traditional talent vetting does not scale for high-impact, high-precision work," said Abhishek Kaushik, CEO and Co-founder of WeCP. "Joining Invisible allows us to extend our assessment frameworks into advanced AI training environments where rigor and accuracy are essential." About Invisible Technologies. Invisible Technologies is building the platform that makes AI work. It adapts models to each business and adds human expertise when needed - the same approach used to improve models for over 80% of the world's top AI companies, including Microsoft, AWS, and Cohere. Invisible works across industries - from supply chain automation for Swiss Gear, to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets. Profitable for over half a decade, was ranked #2 fastest-growing AI company in 2024, and recently raised $100M to advance its platform technology About WeCP. Founded in India by Abhishek Kaushik and Mohit Goyal, alumni of NIT Trichy, WeCP is an AI-native technical assessment platform that designs structured, validated evaluation frameworks to measure real-world expertise across engineering, data science, machine learning, cloud infrastructure, cybersecurity, finance, and advanced STEM roles.
Invisible Technologies agrees to acquire WeCP to strengthen expert validation for high-precision AI workflows. Invisible Technologies today announced it has entered into an agreement to acquire WeCP SAN FRANCISCO & BENGALURU, India-(BUSINESS WIRE)-Invisible Technologies today announced it has entered into an agreement to acquire WeCP, an AI-native technical assessment and intelligence platform known for its rigorously validated evaluation frameworks. As AI systems are deployed across engineering, healthcare, finance, and other complex domains, the quality of the experts shaping those systems has become increasingly critical. High-stakes AI workflows require structured, high-fidelity validation of domain specialists at scale. WeCP brings an AI-native assessment and intelligence platform, which to date has created over two million real-world technical interviews and more than 18,000 targeted domain and role-specific assessment frameworks across engineering, banking, healthcare, finance, and advanced STEM domains. It also has enhanced infrastructure for RL gyms and task simulation. Built over five years of continuous iteration, the platform enables precise evaluation of advanced technical talent. "This acquisition expands our foundation of high-precision AI training," said Matt Fitzpatrick, CEO of Invisible Technologies. "The performance of advanced AI systems depends on trusted human expertise, and WeCP's assessment engine has built one of the most extensively refined technical assessment libraries in the market. By integrating WeCP into Invisible's AI training platform, Meridial, we're raising the bar on precision and speed for expert evaluation across our platform while also accelerating our capabilities in RL gyms and simulated environments." WeCP was founded by NIT Trichy alumni Abhishek Kaushik, formerly of Google, and Mohit Goyal, formerly of Meta, with a vision to modernize technical evaluation. What started as an effort to improve interview question generation evolved into a comprehensive system for measuring real-world skill, reasoning, and domain expertise. Kaushik and Goyal will join Invisible along with several key members of the WeCP team and continue working on their core mission to advance expert assessment infrastructure. "We built WeCP to solve a fundamental challenge: traditional talent vetting does not scale for high-impact, high-precision work," said Abhishek Kaushik, CEO and Co-founder of WeCP. "Joining Invisible allows us to extend our assessment frameworks into advanced AI training environments where rigor and accuracy are essential." About Invisible Technologies Invisible Technologies is building the platform that makes AI work. It adapts models to each business and adds human expertise when needed - the same approach used to improve models for over 80% of the world's top AI companies, including Microsoft, AWS, and Cohere. Invisible works across industries - from supply chain automation for Swiss Gear, to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets. Profitable for over half a decade, was ranked #2 fastest-growing AI company in 2024, and recently raised $100M to advance its platform technology. About WeCP Founded in India by Abhishek Kaushik and Mohit Goyal, alumni of NIT Trichy, WeCP is an AI-native technical assessment platform that designs structured, validated evaluation frameworks to measure real-world expertise across engineering, data science, machine learning, cloud infrastructure, cybersecurity, finance, and advanced STEM roles.
Invisible Technologies named a Built In 2026 Best Places to Work. Invisible Technologies Jan 6, 2026 SAN FRANCISCO, January 6, 2026 - Invisible Technologies, the AI software platform for the enterprise, has been recognized by Built In as one of the Best Places to Work in 2026. The annual awards honor employers across the U.S. whose benefits and compensation set the standard for today's workforce. Now in its eighth year, Built In's Best Places to Work program celebrates the companies shaping the future of work. In a rapidly evolving AI-first job market, recognition as a Best Place to Work helps employers stand out as trusted brands when candidates turn to tools like ChatGPT and Google AI Overviews to research where to work next. "Today's candidates discover the companies they want to work for using AI tools," said Maria Christopoulos Katris, Founder & CEO of Built In. "Earning a Best Place to Work award not only signals to candidates that you invest in your people, it's a lever to strengthen how AI search tools understand and represent your company's story." The awards reflect Built In's data-driven approach, evaluating companies based on compensation, benefits, and company-wide culture programs. "This recognition reflects what our team builds every day: high-impact AI systems, real ownership, and a culture that trusts smart people to do meaningful work," says kelly minella, VP of talent acquisition at Invisible. "If you want to be close to the problem, the customer, and the impact, it's a great time to explore Invisible." To learn more about the 2026 Best Places to Work program and view all winners, visit https://employers.builtin.com/best-places-to-work/. About Invisible Technologies. Invisible Technologies is the AI software platform for the enterprise. Their end-to-end AI software platform structures messy data, builds digital workflows, deploys agentic solutions, evaluates and measures impact, and mobilizes relevant human experts. Invisible has trained foundation models for more than 80% of the world's leading AI model providers, including Cohere, Microsoft, and AWS, and has the expertise to customize AI for any industry, function, or use case. Invisible makes AI work in the real world. In 2024, the company reached $134M in revenue and was named the #2 fastest growing AI company on the Inc. 5000. That momentum continued in 2025 with recognition on the Deloitte Technology Fast 500. Book a demo. Invisible Technologies, Inc.'ll walk you through what's possible. No pressure, no jargon - just answers.