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Strong employer brand and hybrid mid-level role, but niche GenAI/LangGraph skills reduce candidate density.
Requires deep GenAI, LangGraph and AWS production experience, limiting cross-industry transferability.
Explicit 5–8 year requirement plus many mandatory GenAI, LangGraph, AWS and production skills makes screening strict.
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Own end-to-end design and build of scalable AI automation solutions using LangGraph, LangChain, and AWS AgentCore from discovery through production.
Lead technical decisions post-architecture during builds, ensuring robustness, performance, reliability, and cost management at production scale.
Engage and communicate with internal SMEs and stakeholders, demo solutions to leadership, guide Developers and Associates, and manage issue escalation and debugging in production.
5–8 years total experience with 2–4 years in production GenAI/LLM; specifically 12–24 months experience with multi-agent LangGraph.
Expertise in LangGraph multi-agent state machines, AWS Bedrock model deployment, SQL, Python (advanced), and AI development tools (Claude Code, GitHub Copilot).
Experience owning 3+ AI systems post-deployment with hands-on coding, including debugging production failures and scaling POCs to production.
Located for hybrid work in office 3 days/week; shift 1pm–10pm IST.
Experienced in applying LangGraph and multi-agent AI systems in enterprise-scale AWS environments managing full production lifecycle.
Capable of translating complex business processes into robust AI automation solutions and leading day-to-day build execution and team guidance.
Strong communicator comfortable demoing AI solutions to business leadership and maintaining stakeholder engagement throughout project phases.