Gen AI LeadsArchitect
Job Location:
Atlanta, GA - USA
Monthly Salary:
Posted on:
Vacancies:
Job Summary
Position :: Gen AI Leads/Architect :: Atlanta GA-Hybrid OR Ready to Travel :: Hire Type: Contract(W2)
Project description
Delivery & Architecture
- Own end-to-end delivery of AI-native programs - from architecture through production deployment
- Design and build multi-agent orchestration systems using LangChain LangGraph CrewAI or equivalent
- Integrate agent systems with enterprise surfaces: APIs ERPs CRMs data platforms - not toy datasets
- Define agent topology: tool routing memory strategy state machines fallback handling
Agentic Coding & Development
- Run agentic coding workflows using Claude Code Cursor OpenAI Codex or equivalent CLI tools
- Lead projects where AI writes significant portions of the codebase - and you guide review and ship it
- Work with shared context frameworks and multi-session agent setups for team use
- Debug non-deterministic agent outputs systematically - not by gut feel
Client & Stakeholder Engagement
- Translate business problems into agent architectures for global CXO-level stakeholders
- Run discovery workshops solution reviews and delivery cadences with client teams
- Prepare and present technical proposals POC plans and roadmaps - own the story end-to-end
Team & Practice
- Mentor junior AI engineers; raise AI engineering quality across the delivery team
- Stay current: evaluate new models frameworks and tooling before the hype catches up
- Contribute to internal knowledge bases reusable frameworks and accelerators
Skills
| Agent Orchestration LangChain LangGraph CrewAI - not just conceptual | Agentic Coding Tools Claude Code CLI Cursor OpenAI Codex Copilot |
| RAG & Vector Stores Chroma Weaviate Pinecone - knows where RAG breaks | LLM APIs & SDKs Anthropic OpenAI Gemini - prompt design tool use |
| Python / TypeScript Primary languages for agent backend development | LangSmith / Observability Tracing evaluation debugging agent runs |
| Cloud Platforms Azure AWS GCP (at least one) - deployment infra managed services | API & System Integration REST gRPC Kafka - enterprise integration patterns |
| MCP / Shared Context Model Context Protocol Beads | Agent Evaluation Testing non-deterministic outputs guardrails evals |
| CI/CD & DevOps Git containers pipelines - agents need to ship | Client Communication Can present architecture to a CXO without jargon |
What You Must Have Actually Done
Not just what you know. What you have shipped.
- Deployed 2 3 agent-based systems in production - stateful multi-step real users
- Used LangGraph for multi-agent orchestration with memory tool routing and state management
- Built projects where AI (Claude Code Codex Cursor) wrote significant portions of the code
- Implemented RAG pipelines end-to-end - chunking embedding retrieval re-ranking evaluation
- Integrated agents with real enterprise APIs - not just OpenAI playground or sample data
- Debugged a production agent failure - and fixed it without blaming the model
- Can articulate when NOT to use agents - that is how we know you have built things
Bonus - Real Differentiators
- Experience with Claude Code CLI in team environments ( shared context multi-session flows)
- Familiarity with LangSmith for agent tracing evaluation pipelines and debugging at scale
- Has shipped something using MCP (Model Context Protocol) or similar shared-context tooling
- QA/testing mindset for agents - systematic evaluation of non-deterministic outputs
- Background in IT services or consulting - managing client expectations while building
- Experience with SLMs fine-tuning or on-device/edge agent deployment
What We Are Not Looking For
- Someone who lists LLMs on a resume but has only called the API in a Jupyter notebook
- AI enthusiasts whose hands-on experience is less than a year old
- People who explain everything in terms of frameworks they have never deployed
- Consultants who can only narrate what others have built
