Applied AI Solutions Architect
phData
Applied AI Solutions Architect
phData
Managed data engineering and ML solutions
Join phData, a remote-first data and AI consultancy company with employees across the United States, Latin America, and India. We partner with industry leaders, including Snowflake, AWS, Anthropic, Glean, and dbt, to solve the complex data and AI challenges that slow large enterprises.
We're growing fast, and we give our people real ownership over their work. We hire top performers and trust them to deliver results.
Why phData?
We are looking for an Applied AI Solutions Architect to join our Applied AI team in our Agentic Delivery Center. In this role, you will lead the architecture and hands-on implementation of high-impact, production-ready agentic AI solutions that reason, retrieve, act, and integrate with enterprise systems to deliver measurable business outcomes. You will partner closely with clients, forward-deployed engineers, data engineers, and platform teams to design reusable accelerators, set technical standards, and deliver high-quality engagements that drive real business results.
Key Responsibilities
Agentic Architecture & Client Delivery
● Own and drive end-to-end architecture, solution design, and delivery of agentic AI solutions for enterprise clients across diverse industries.
● Design and build reusable agentic accelerators and reference architectures aligned with the Intelligence Platform that can be deployed across multiple clients in a fixed-price format.
● Translate ambiguous business problems into clear agentic solution designs that align with the phData Intelligence Platform, methodologies, standards, and best practices.
● Architect production-grade agents emphasizing reliability, scalability, security, observability, and evaluation and guardrail strategies for safe, accurate performance. before and after deployment.
● Ensure engagements are delivered on time, within scope, and with measurable business value for clients.
Collaboration & Leadership
● Collaborate with others to shape the architectural standards for how agentic capabilities and accelerators are built and deployed at clients.
● Design and build reusable agentic accelerators and reference architectures aligned with the Intelligence Platform that can be deployed across multiple clients.
● Establish the foundation of our India Agentic Delivery Center, by developing patterns, tooling, and ways of working that scale.
● Engage with cross-functional partners, including forward-deployed engineers, data scientists, data engineers, platform/DevOps engineers, and business stakeholders, to deliver successful client engagements.
● Ensure high quality in deliverables through code reviews, documentation, testing, governance, and adherence to security and compliance standards.
● Partner with practice and account leaders to identify opportunities to expand engagements, improve delivery, and standardize patterns for deploying and operating AI solutions.
Practice & Firm Contribution
● Contribute to internal initiatives such as IP development, accelerators, reference architectures, templates, playbooks, and training related to AI engineering.
● Represent phData with professionalism in all interactions, communicating clearly with both technical and non-technical stakeholders. Additional Responsibilities
● Act as a trusted advisor to senior client stakeholders, shaping roadmaps, influencing strategic decisions, and guiding long-term initiatives.
● Mentor and coach team members, fostering a culture of learning, feedback, and continuous improvement.
● Help define and refine practice standards, reusable assets, and delivery frameworks.
About You
You are a technical leader and client-focused consultant who enjoys turning complex, ambiguous problems into robust, production-ready agentic systems. You are opinionated and prescriptive about how good agents are built, comfortable working across data, infrastructure, and application layers, and energized by a zero-to-one environment where you are the technical bar. You thrive in an outcomes-driven environment, partnering with clients to engineers to design and build architectures that are performant, secure, scalable, and maintainable.
Required Qualifications Experience
6+ years of experience as an AI Engineer, Machine Learning Engineer, Software Engineer, or Data Engineer building and deploying production AI/ML solutions, including recent hands-on experience building LLM-powered or agentic applications.
Technical / Functional Skills
● Hands-on understanding of Large Language Models, agentic architectures, and retrieval frameworks (RAG), including prompt design, context engineering, and tool/function calling
● Experience with LLM orchestration frameworks (e.g. LangChain, LlamaIndex) and the broader agentic stack, such as multi-agent patterns, memory, planning, and protocols (e.g. MCP)
● Experience designing evaluation, guardrail, and observability strategics for LLM and agent systems (LLMOps/AgentOps)
● Hands-on experience in modern programming languages, such as Python, including developing APIs
● Deep expertise in cloud-native AI/ML platforms (e.g. AWS Bedrock and SageMaker, Azure AI/ML, Snowflake Cortex) with proven experience deploying solutions into production
● Complete software development lifecycle experience including design, documentation, implementation, testing, deployment, and ongoing operations
● Demonstrated use of AI-assisted development tooling to accelerate delivery while maintaining quality
● Strong working knowledge of SQL and the ability to write, debug, and optimize complex and distributed queries.
Consulting / Delivery Skills
● Experience delivering projects for external or internal clients in a professional services or consulting environment, ideally in a fixed-bid capacity.
● Ability to break down ambiguous problems into structured, actionable steps and drive them through to completion. ● Excellent written and verbal communication English., with experience presenting technical solutions to clients and facilitating discussions with both technical and business stakeholders.
Collaboration & Ownership
● Demonstrated ability to work effectively with distributed and cross-functional teams across the US, LATAM, and India.
● Proven track record of taking ownership, managing multiple priorities, and delivering high-quality work with minimal supervision.
● Experience building reusable accelerators, modular codebases, or products deployed across multiple clients.
● Industry experience building AI/ML solutions in life sciences, retail, financial services, or manufacturing
● Prior experience working in global or remote teams and partnering across US, LATAM, and/or India.
● Contributions to open source technology stacks, technical communities, speaking, or writing related to AI and agents are a plus.
Education
● Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience preferred.
phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.
phData provides data engineering, data strategy, and machine learning solutions through end-to-end managed services and consulting for enterprises. It delivers cloud data engineering, data migrations, business intelligence, and ML applications by combining data infrastructure automation with analytics and AI strategy in project-based engagements and ongoing support. It differentiates itself by offering full, service-led delivery focused on sustainable data engineering practices and strong customer success, plus its status as an AWS consulting partner with specialized cloud analytics and ML expertise on AWS. Its goal is to help clients turn data into actionable insights and sustainable growth by building scalable data platforms and AI systems guided by clear roadmaps.
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