Tech Lead / Lead Architect - RAG & Agentic AI - JPMC

Tech Lead / Lead Architect – RAG & Agentic AI

Location: Columbus, OH/ Wilmington, DE – 3 days onsite role

Long Term Project

Role Summary: Lead architecture, design, and delivery of Agentic AI and RAG-based solutions, partnering with customers and internal teams to build scalable, secure, and high-impact AI systems.

Must-Have:

Strong experience in RAG pipelines, embeddings, vector DBs, LLM orchestration, and prompting techniques.

Hands-on expertise in AWS (Lambda, API Gateway, Bedrock, S3, OpenSearch, IAM, VPC, Secrets Manager).

Ability to design end-to-end AI architecture and build PoCs before committing solutions to customers.

Deep understanding of AI guardrails (toxicity, hallucination control), data privacy, and cloud security patterns.

Proven ability to lead from the front, mentor teams, and own delivery under tight timelines and high visibility.

Strong customer communication skills – ability to explain architecture, trade-offs, and risks clearly.

Experience handling model evaluation, observability, performance tuning, and cost optimization in production AI systems.

Expertise in API design, microservices integration, and event-driven architectures for AI systems.

Good-to-Have:

Experience with Agentic AI frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel, etc.).

Exposure to marketing domain use cases (campaign optimization, personalization, analytics, insights).

Familiarity with multi-agent orchestration, tool usage (MCP), and human-in-loop workflows.

Screening Checklist (Quick Evaluation for Interviews)

Use this to quickly filter candidates:

Technical Fit

Can clearly explain a RAG architecture (data ingestion embedding retrieval generation)

Has built or deployed production AI/LLM solutions (not just POCs)

Understands agent lifecycle, orchestration, and tool integrations

Demonstrates AWS architecture + security (IAM roles, network isolation, secrets)

Knows prompt engineering + evaluation + guardrails implementation

Architect & Leadership Fit

Has led architecture/design discussions with customers

Can drive PoC production transition independently

Shows ownership mindset (decision-making without dependency)

Can mentor/coach developers and review designs/code

Communication & Behavioral Fit

Explains complex AI topics in simple, structured way

Asks insightful, strategic questions

Demonstrates ability to handle ambiguity and pressure