Job Title: Tech Lead / Lead Architect – RAG & Agentic AI
Location: Columbus, OH/ Wilmington, DE – 3 days onsite role
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
Maddula Venkateshwara Reddy | ICS Global Soft
Senior. US IT RECRUITER
venkatreddy61996@gmail.com