Tech Lead / Lead Architect – RAG & Agentic AI Urgent Need

Tech Mirrors; Columbus (OH); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Tech Mirrors is looking for a Tech Lead / Lead Architect in Columbus, OH. You will lead the architecture, design, and delivery of Agentic AI systems while mentoring teams and ensuring high-quality outputs. The role requires strong experience in RAG pipelines and AWS technologies.

Key responsibilities include designing scalable AI architecture, leading discussions with customers, and ensuring effective communication of technical concepts. This role offers the chance to work on long-term projects in a cutting-edge domain.

Qualifications

• Strong experience in RAG pipelines, embeddings, and vector DBs.
• Hands-on expertise in AWS technologies.
• Ability to design and build AI architecture.

Responsibilities

• Lead architecture and delivery of AI systems.
• Mentor teams and own delivery under tight timelines.
• Ensure communication of complex architecture to customers.

Skills

RAG pipelines

AWS (Lambda, API Gateway, Bedrock)

AI architecture design

Customer communication

Model evaluation

API design

Job description

Tech Lead / Lead Architect - RAG & Agentic AI

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

Long Term Project

Strong financial and banking domain experience required.

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)

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 questionsDemonstrates ability to handle ambiguity and pressure