GenAI Architect

We are seeking a GenAI Architect who will translate the customer's AI-driven SDLC roadmap into a clear target architecture, detailed design, and phased implementation plan.

Experience: 8-15 Years

Roles and Responsibilities:

• Design and implement the agentic framework and agent orchestration layer for SDLC use-cases using LangGraph (preferred) and LangChain where appropriate.
• Define the right approach per use case: tool calls vs. MCP servers vs. agents, including routing/orchestration patterns and multi-agent collaboration.
• Work with a small team (2 members) to build, test, deploy, and operate a portfolio of MCP servers, tools, and agents.
• Implement robust LLM integration patterns: prompt/agent design, context & memory management, guardrails, fallback strategies, and cost/latency optimization.
• Establish evaluation and quality gates for AI in the SDLC: automated tests, regression evals, golden datasets, and CI integration.
• Set up observability & operations: logging, tracing, prompt/version tracking, usage analytics, and runbooks.

Produce enablement assets for Claude Code adoption:

• claude.md, memory.md, agent/tool conventions, repo templates
• How-to guides for agents, hooks, workflows, and team best practices
• Partner with engineering/security on data privacy, secrets management, and policy compliance.

Required experience

• 10+ years in software engineering / IT with strong architecture + hands-on delivery.
• 2+ years building with GenAI/LLMs in production (agents, tool use, RAG, orchestration).
• Strong LangGraph experience (state machines, multi-agent flows, human-in-the-loop), plus LangChain for tooling/integrations.
• Demonstrated experience adopting Claude Code in advanced usage (agents, hooks, workflows, repo conventions) and coaching teams.
• Strong engineering fundamentals: APIs, CI/CD, testing strategy, SDLC tooling, cloud basics.
• Working knowledge of classical ML concepts (certification a plus, not required).

Nice to have

• Experience building/operating MCP servers and tool ecosystems.
• Experience with enterprise security/compliance, data governance, and red teaming.
• Experience with developer productivity platforms and SDLC automation (GitHub/GitLab, Jira, code review automation).

Deliverables:

• Target architecture + detailed design docs for AI-accelerated SDLC using Claude Code + LangGraph orchestration.
• Working MCP/tool/agent implementations with CI, evals, and monitoring.
• Playbooks/templates (claude.md, memory.md, orchestration patterns) and concise enablement documentation.