Full-Time
Senior Forward Deployed AI Engineer
Enterprise
Updated on 5/7/2026
Scale AI
5,001-10,000 employees
AI data platform for generative models
Compensation Overview
$216k - $315k/yr
San Francisco, CA, USA + 1 more
More locations: New York, NY, USA
In Person
 Sales & Solution Engineering (1) |
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- 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
- Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
- Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
- Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
- Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences
- Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
- Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
- Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
- Deploy and configure AI models and agents within customer security and compliance boundaries
- Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
- Architect multi-agent systems that orchestrate between different models, tools, and data sources
- Implement evaluation frameworks to measure agent performance and iterate toward business objectives
- Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement
- Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
- Build and maintain prompt libraries, templates, and best practices for customer use cases
- Conduct systematic prompt experimentation and A/B testing to improve model outputs
- Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate
- Serve as the primary technical point of contact for strategic enterprise accounts
- Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
- Provide technical training and knowledge transfer to customer teams
- Work closely with Scale's product and engineering teams to translate customer needs into product improvements
- Document technical architectures, integration patterns, and best practices
- Debug complex technical issues across the entire stack, from data pipelines to model outputs
- Rapidly prototype solutions to unblock customers and prove out new use cases
- Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
- Identify opportunities for productization based on common customer patterns
- Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
- Experience building and deploying AI agents or autonomous systems in production
- Knowledge of vector databases and semantic search systems
- Contributions to open-source AI/ML projects
- Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
- Experience using Terraform, Bicep, or other Infrastructure as Code tools
- Previous work in a devops, platform, or infra role
- Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)
- Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
- Domain expertise in verticals like finance, healthcare, government, or manufacturing
- Experience with technical enablement or teaching programs
Scale AI provides a platform for accelerating AI development by helping organizations harness their data to customize powerful generative models. The Scale Generative AI Platform offers data collection, curation, and annotation tools, plus evaluation and optimization features to improve model performance. It serves a wide range of customers from technology giants (Microsoft, Meta) and enterprises (Fox, Accenture) to other AI companies (OpenAI, Cohere), government agencies (U.S. Army, Air Force), and startups (Brex, OpenSea). Revenue comes from subscriptions and services tied to the platform and tooling, aimed at enhancing the performance and safety of leading large language models and generative models.
Company Size
5,001-10,000
Company Stage
Acquired
Total Funding
$15.9B
Headquarters
San Francisco, California
Founded
2016
Simplify's Take
What believers are saying
- ICG Solutions acquisition on April 20, 2026, integrates LUX for DoD real-time intelligence analytics.
- BAE Systems partnership on March 27, 2026, embeds agentic AI into combat vehicles and deterrence programs.
- $1B funding in May 2024 from Amazon and Meta boosts valuation to $14B for frontier AI expansion.
What critics are saying
- Outlier workers scrape Facebook and Instagram data, triggering GDPR and CCPA lawsuits by Q4 2026.
- Snorkel AI's programmatic labeling cuts human needs by 80%, eroding Scale's startup market share.
- OpenAI builds in-house data engine, eliminating 40% of Scale's generative AI revenue within 12 months.
What makes Scale AI unique
- Scale Data Engine manages full ML lifecycle with 100,000 annotators for 35% higher accuracy.
- Scale Generative AI Platform enables enterprise customization of LLMs without third-party data sharing.
- Voice Showdown benchmarks voice AI models across 60+ languages in real-world Dictate and Speech-to-Speech modes.
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Benefits
Health, Dental & Vision Coverage - Our health plans give you the flexibility to select the right coverage for you and eligible family members through a variety of plan options.
Easy to use 401(K) - Plan and invest for the future with a 401(k) via Guideline. Scale’s 401(k) plan provides you an opportunity to defer compensation for your long-term savings.
Wellness Fund - We care about the physical, mental, and emotional wellbeing of all Scaliens. Our $100/month wellness stipend can be used for gym memberships, acupuncture, meditation apps, and so much more.
Virtual Social Activities - Being remote has not stopped us from hosting fun virtual events. From trivia night to candle making, we ensure employees are fostering connections & building strong relationships.
Learning & Development - We know how important career growth is for Scaliens, so we offer a $500/year L&D stipend to help support continued development throughout your journey.
Flexible hours allow you to work when you are most productive. You can work with your manager to best plan your daily work schedule.
Generous Paid Time Off - Enjoy time to travel or plan a staycation. We encourage employees to take time off to recharge and prevent burnout. We have a flexible PTO policy where each employee is afforded the flexibility to take planned time-off as needed.
Commuter Benefits - Set aside pre-tax dollars to use on qualified transportation expenses to help ease your commute.
Parental Leave - Balancing work and family is essential, and Scale understands the importance of having adequate leave policies in place to promote a healthy home and work life.
Growth & Insights and Company News
6 month growth
↓ -1%1 year growth
↑ 0%2 year growth
↑ 3%Scale AI acquires ICG Solutions to provide the U.S. Department of War and the broader Intelligence Community the most advanced, reliable AI infrastructure available.
Meta-linked Scale AI faces scrutiny over data scraping by gig workers. Contractors say tasks went beyond training models into handling personal and sensitive data. AI training under scrutiny as workers flag data scraping and ethical concerns * AI gig workers raise concerns over data use and working conditions * Tasks reportedly included social media scraping and sensitive content * Industry faces growing questions over ethics and transparency The rapid rise of artificial intelligence has created a vast, largely unseen workforce tasked with training the systems that power it. But new accounts from workers linked to Scale AI suggest the reality of that work may be more complicated than advertised. Scale AI, partly owned by Meta, runs a platform called Outlier, where contractors are recruited to help refine AI models. The work is often pitched as flexible, skilled employment for people with backgrounds in fields such as medicine, economics and science. However, several workers say the tasks extended well beyond technical training. Instead, they described assignments involving scraping social media platforms like Facebook and Instagram, tagging individuals and analysing personal content. One contractor reportedly said users would be surprised to know how their data was being handled. "I don't think people understood quite that there'd be somebody... looking at your profile, using it to generate AI data," they said, as quoted in a news report. From expert tasks to uncomfortable assignments. Workers who spoke about their experience said the nature of assignments could vary widely, and at times become difficult to handle. Some described being asked to transcribe explicit audio content or label distressing images. Others said they encountered material they had not expected, including violent scenarios or sensitive imagery. One doctoral student said they had been assured certain content would not appear, but later encountered otherwise. "We had already been told... no nudity... no gore," they reportedly said. "But then I would get an audio transcript thing for porn," as quoted in a news report. Beyond content concerns, there were also questions about how data was sourced. Several workers said they were asked to analyse publicly available social media profiles, including identifying people, locations and relationships. Some assignments, they claimed, appeared to involve data from younger users as well. A source familiar with the company's operations said tasks do not involve private accounts and that contributors are not required to engage with material they find uncomfortable. A growing industry with blurred lines. The scale of this kind of work is expanding quickly. Glenn Danas, a lawyer representing AI gig workers, estimates that hundreds of thousands of people globally are now involved in similar roles across platforms. Many workers said they took on the work as a way to supplement income, particularly in a labour market where AI itself is beginning to reshape job opportunities. At the same time, concerns about pay and conditions have emerged. Some workers described inconsistent earnings and a project-based system where tasks could disappear without notice. Others alleged recruitment practices that promised higher pay than what was ultimately offered, though the company has disputed this. There were also reports of monitoring software being used during tasks. Workers said tools could track activity and capture screenshots, while a source said such systems are intended to ensure accurate payment rather than continuous surveillance. Scale AI has said its platform offers flexible, project-based work and that contributors can choose when and how they participate. Questions over data, ownership and the future. The situation highlights a broader issue facing the AI industry. As models grow more advanced, the demand for large volumes of labelled data continues to increase. That data often comes from real-world sources, raising questions about consent, ownership and usage. Scale AI has worked with major technology firms including Google and OpenAI, as well as government clients. Some workers said they believed their tasks were contributing to training systems used across the industry. At the same time, many expressed uncertainty about what exactly they were helping to build. One worker reportedly questioned why certain tasks were necessary, noting that some appeared repetitive or unclear in purpose. Despite these concerns, most said they continue to take on assignments. For many, the work remains one of the few accessible options in a changing job market shaped increasingly by automation. "I have to be positive about AI because the alternative is not great," one worker reportedly said. The debate around AI is often framed in terms of future potential. But for those already working behind the scenes, the questions appear more immediate - about how data is used, how workers are treated, and where the boundaries should be drawn. All-Inclusive Resort in Riviera NayaritResort on Punta de Mita's stunning beaches. All-inclusive: food, cocktails, and activities at Grand Palladium Vallarta. Plus, a laid-back paradise for surfers!Palladium Hotel Group | Sponsored
Qatar eyes a bigger role in AI with full-stack investments. Doha, Qatar - Qatar is building its artificial intelligence strategy across multiple layers of the technology stack, combining sovereign investment, talent development, startup support, and domestic computing infrastructure as it works to position itself as a regional hub for AI. Recent activity around Web Summit Qatar 2026 points to a coordinated approach that goes beyond backing individual companies and instead focuses on building an ecosystem that can support AI development, deployment, and commercial adoption over time. Investing from hardware to inference. One of the clearest signs of that strategy is the role of the Qatar Investment Authority, which has been backing companies involved in core AI infrastructure. In November 2025, QIA joined d-Matrix's $275 million Series C round, supporting a company focused on generative AI inference for data centers. In March 2026, QIA also announced an investment in Ayar Labs, whose co-packaged optics technology is designed to improve the speed and efficiency of next-generation AI computing systems. Together, those moves show QIA is not only targeting AI applications, but also critical enabling technologies deeper in the compute stack. This matters because countries seeking to build sovereign AI capabilities increasingly need more than access to models. They also need exposure to the hardware, networking, and inference technologies that determine performance, cost, and scalability. Qatar's investment pattern suggests it is seeking strategic visibility into those layers while building relationships with companies that could shape future regional deployments. Building the talent base. At the same time, Qatar is putting visible effort into growing the human capital needed to sustain an AI economy. In February 2026, Qatar Foundation and Scale AI launched a partnership focused on capacity-building, innovation activities, and pathways that support Qatar's AI goals, including the exploration of a regional hub for AI development. That initiative reflects a broader recognition that long-term AI competitiveness depends not only on capital and infrastructure, but also on a workforce able to build, train, deploy, and govern advanced systems. That talent agenda is also extending into deep-tech entrepreneurship. QIA and QRDI Council are supporting the launch of DEEP Qatar, an expansion of ESMT Berlin's Institute for Deep Tech Innovation, aimed at helping researchers, startups, and innovators turn scientific advances into scalable businesses. The initiative adds another layer to Qatar's ecosystem strategy by linking research, commercialization, and investment rather than treating them as separate tracks. Expanding local AI infrastructure. Qatar's AI ambitions are also being matched by local infrastructure build-out. Ooredoo launched sovereign AI cloud services in Qatar in 2025 using NVIDIA accelerated computing hosted in local data centers, and in early 2026 its data center arm Syntys expanded its footprint through the acquisition of two facilities in the country. More recently, Oracle and Ooredoo announced a collaboration to deliver sovereign AI and cloud services locally, aimed at helping government and enterprise customers build AI-powered applications while meeting data sovereignty requirements. That local compute layer is especially important for a country trying to serve domestic institutions and regulated sectors while also building regional relevance. Qatar's model appears to be centered on creating in-country capacity first, then using that capacity to support public-sector transformation and private-sector adoption. From strategy to application. On the policy side, Qatar's AI push continues to build on its national AI strategy and the government-led GovAI program, which is designed to accelerate AI adoption across public entities and translate national policy into real-world use cases. Current examples highlighted by MCIT include projects linked to tourism and labor compliance, underscoring that Qatar's AI efforts are not limited to investment announcements or summit-stage visibility but are also feeding into public-service delivery. This application layer is becoming increasingly important. Infrastructure on its own does not create an AI economy unless it is matched by demand from businesses, governments, and startups. Qatar's approach suggests it is trying to build those layers in parallel: backing enabling technologies abroad, expanding local compute capacity, and encouraging domestic institutions to adopt AI in ways that can create lasting demand. A long-term ecosystem play. Rather than forcing immediate localization from every company it backs, Qatar appears to be pursuing a longer-term model. The emphasis is on building relationships across the global AI value chain while preparing the domestic conditions needed for those ties to translate into local economic activity later. That includes training talent, strengthening research commercialization, supporting deep-tech entrepreneurship, and ensuring that sovereign infrastructure is in place when demand scales. As global competition around sovereign AI intensifies, Qatar's strategy is taking shape as an ecosystem play rather than a single bet. Its ambitions now extend from semiconductor-adjacent infrastructure and inference platforms to startup development, education partnerships, and local AI cloud capacity. The result is a broader attempt to secure a role not just as an investor in AI, but as a market where AI technologies can be developed, deployed, and commercialized over time. 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BAE Systems and Scale AI partners on AI defense missions and platforms. March 27, 2026 BAE Systems and Scale AI formed a strategic partnership that seeks to accelerate the development and deployment of the latest in advanced agentic artificial intelligence technology. BAE Systems, a leading defense and security company, has formed a strategic partnership with Scale AI, a leading artificial intelligence technology company, to utilize its technology, including its Data Engine and Generative AI Platform, in the development of intelligent artificial intelligence technology in combat vehicles, deterrence technology, and future defense technology. "Modern warfare is won at the speed of data," said Peder Jungck, Chief Innovation & Strategy Officer for the Intelligence & Security sector at BAE Systems. "By teaming with Scale AI, we are ensuring that the Department of War has access to the world's most advanced agentic tools, to create intelligent, adaptive systems that can out-think and outpace the adversaries." "We're proud to collaborate with BAE Systems to bring agentic AI capabilities to America's most critical military platforms," said Zane Teeters, Head of Public Sector GTM, Scale AI. "The value of this agreement is ensuring that human operators have the most advanced AI capabilities available on today's platforms and systems, dramatically accelerating the time to mission impact for the Department of War."
Agentic AI capabilities to be integrated into defense platforms by BAE Systems, Scale AI. March 27, 2026 Technology Editor Military Embedded Systems FALLS CHURCH, virginia. BAE Systems and Scale AI have signed a strategic relationship agreement to speed the development and fielding of agentic artificial intelligence capabilities for Department of War mission environments and operational platforms, the company announced in a statement. The collaboration combines BAE Systems' work in defense operations, systems integration, and platforms with Scale AI's data and generative artificial intelligence tools, the statement reads. The two companies plan to embed those capabilities into the architecture of combat vehicles, deterrence programs, and future platforms used by the Department of War, according to the statement. BAE Systems says the effort is aimed at building systems that can support operators in high-stakes environments by processing information and adapting during missions. The company describes the work as part of a broader push to bring artificial intelligence tools closer to where military operations are carried out, the statement says. The release also points to BAE Systems' Aided Target Recognition capability as an example of how artificial intelligence can turn sensing data into coordinated effects across distributed forces, according to the statement. That approach is intended to support faster decisions and sustain operations in contested environments, the company says. Featured companies. 1101 Wilson Boulevard