The Role
Leads hands-on applied AI proofs of concept from research hypothesis or business need through evaluation and technical handoff. Designs architectures and builds prototypes using LLMs, RAG, agents, machine learning, multimodal AI, enterprise data, APIs, and integrations. Develops evaluation frameworks, compares technical alternatives, documents reproducible results, identifies reusable components, and provides scale or stop recommendations. Coordinates cross-functional specialists and mentors AI engineers, POC engineers, and interns.
Summary Generated by Built In
POC Technical Lead, Applied AI
About the Role
WRL is looking for a hands-on POC Technical Lead, Applied AI to turn validated research hypotheses and enterprise business problems into working, measurable, and transfer-ready AI prototypes.
You will work at the intersection of applied AI research, solution architecture, and rapid prototyping. Partnering with researchers, domain specialists, business stakeholders, and engineering teams, you will design prototype architectures, build end-to-end proofs of concept, evaluate technical alternatives, and determine whether a solution is ready to move into development.
This is not a coordination-only or presentation-focused role. You will write and review code, integrate AI models with enterprise data and systems, build evaluation frameworks, and lead the technical execution of PoCs.
Once a PoC is validated, you will prepare the architecture, code, evaluation evidence, technical documentation, and implementation recommendations required for Winfo’s Development and Deployment teams to productize and scale the solution.
What You’ll Do
- Translate research hypotheses and business requirements into focused, time-bound POC plans.
- Define the minimum prototype needed to test technical feasibility and potential business value.
- Design end-to-end architectures for applied AI, generative AI, and agentic solutions.
- Build working PoCs using LLMs, RAG, agents, machine learning, multimodal AI, knowledge graphs, APIs, and enterprise integrations.
- Compare models, frameworks, prompting strategies, retrieval methods, and architecture alternatives using measurable evidence.
- Build evaluation harnesses covering quality, groundedness, robustness, latency, cost, safety, and operational complexity.
- Integrate prototypes with representative enterprise data, applications, APIs, and workflows.
- Ensure that code, configurations, prompts, datasets, experiments, and evaluation results are documented and reproducible.
- Identify reusable components, technical patterns, and potential WRL accelerators.
- Produce clear technical handoffs for Development and Deployment teams.
- Coordinate contributions from AI, engineering, data, cloud, security, product, and domain specialists.
- Mentor AI engineers, POC engineers, and interns.
- Provide technical evidence for decisions to scale, revise, pivot, replicate, transfer, or stop a PoC.
The WRL operating model progresses qualified opportunities through Research, POC, Decision, and Transfer, with the POC leadership role accountable for prototype architecture and technical handoff.
What You’ll Bring
- Proven experience designing and building end-to-end AI or machine-learning PoCs.
- Strong hands-on proficiency in Python and modern AI development frameworks.
- Experience with LLMs, RAG, agentic AI, APIs, data pipelines, and enterprise integrations.
- Ability to convert ambiguous research or business requirements into a working prototype and measurable evaluation plan.
- Strong understanding of machine learning, generative AI, model evaluation, and software-engineering fundamentals.
- Experience comparing models, technologies, platforms, and architectures using evidence.
- Practical knowledge of source control, testing, code review, containers, APIs, cloud platforms, and technical documentation.
- Experience working with researchers, software engineers, data engineers, cloud architects, security teams, and product teams.
- Strong communication skills with the ability to explain technical decisions, risks, costs, limitations, and trade-offs.
- Evidence of taking at least one AI initiative from concept through prototype and engineering or production handoff.
Preferred Qualifications
- Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field.
- Experience with OCI, Azure, AWS, or Google Cloud.
- Familiarity with MCP, multi-agent orchestration, vector databases, knowledge graphs, MLOps, LLMOps, and AI observability.
- Experience integrating AI with Oracle, SAP, Salesforce, or comparable enterprise platforms.
- Experience creating reusable AI accelerators, reference architectures, or internal platforms.
- Exposure to healthcare, life sciences, BFSI, or other regulated industries.
- Contributions to open-source projects, technical publications, patents, white papers, or developer communities.
- Experience mentoring engineers or leading small cross-functional technical teams.
What Success Looks Like
- PoCs answer clearly defined business and technical questions.
- Prototype results are measurable, reproducible, and supported by evidence.
- Weak approaches are identified before significant production investment.
- Successful PoCs are transferred with clear architecture, code, evaluation results, risks, and implementation recommendations.
- Reusable components and patterns are identified across customer use cases.
- WRL develops a disciplined and repeatable POC capability.
Who You Are
You are:
- A hands-on builder who also thinks architecturally
- Comfortable working with ambiguity and incomplete information
- Disciplined about experimentation, evidence, and evaluation
- Able to distinguish a polished demonstration from a validated PoC
- Provider-agnostic and pragmatic about technology choices
- Conscious of quality, latency, cost, security, and maintainability
- Effective across research, engineering, business, and customer teams
Why Join Winfo Research Labs?
You will join WRL at an early stage and help establish how enterprise AI ideas are converted into validated and reusable solutions.
You will work across frontier AI, customer innovation, technical experimentation, and enterprise architecture, with the opportunity to see successful prototypes move into real customer environments.
Own the journey from validated research hypothesis to working, evaluated, and transfer-ready AI prototype.
Skills Required
- Proven experience designing and building end-to-end AI or machine-learning proofs of concept
- Strong hands-on proficiency in Python and modern AI development frameworks
- Experience with LLMs, RAG, agentic AI, APIs, data pipelines, and enterprise integrations
- Ability to convert ambiguous research or business requirements into a working prototype and measurable evaluation plan
- Strong understanding of machine learning, generative AI, model evaluation, and software-engineering fundamentals
- Experience comparing models, technologies, platforms, and architectures using evidence
- Practical knowledge of source control, testing, code review, containers, APIs, cloud platforms, and technical documentation
- Experience working with researchers, software engineers, data engineers, cloud architects, security teams, and product teams
- Strong communication skills for explaining technical decisions, risks, costs, limitations, and trade-offs
- Evidence of taking at least one AI initiative from concept through prototype and engineering or production handoff
- Bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, or a related field
- Experience with OCI, Azure, AWS, or Google Cloud
- Familiarity with MCP, multi-agent orchestration, vector databases, knowledge graphs, MLOps, LLMOps, and AI observability
- Experience integrating AI with Oracle, SAP, Salesforce, or comparable enterprise platforms
- Experience creating reusable AI accelerators, reference architectures, or internal platforms
- Exposure to healthcare, life sciences, BFSI, or other regulated industries
- Contributions to open-source projects, technical publications, patents, white papers, or developer communities
- Experience mentoring engineers or leading small cross-functional technical teams
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The Company
What We Do
Winfo Solutions is an AI innovation-led digital transformation company that helps organizations modernize operations, accelerate growth, and unlock value from data, automation, cloud, and enterprise technologies. It delivers Oracle transformation, AI-powered innovation, intelligent automation, data engineering, analytics, business intelligence, cloud modernization, managed services, and custom application development for global enterprises across industries seeking stronger business outcomes and modernized technology environments.
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