Automation and AI Developer

Are you passionate about Automation and AI and eager to make a significant impact? We are seeking a highly motivated Automation & AI Solutions Lead with strong organizational and technical skills. You will work closely with architects, developers, and business stakeholders to translate real-world problems into robust AI systems. The role demands deep expertise in LangGraph, LangChain, and AWS-based deployments, with accountability from discovery through production. Success in this role means delivering reliable, scalable AI solutions that create measurable business impact.

Job description:

In this role as an Automation and AI Developer, you will:

• Engage internal SMEs to understand current processes and as-is workflows - translate into buildable AI requirements.
• Demo working solutions to internal stakeholders up to business leadership level.
• Support the Architect during feasibility and POC phases - contribute to rapid builds and validate fit.
• Maintain stakeholder communication throughout: progress updates, issue escalation, solution walkthroughs.
• Co-invest with the Architect in upfront solution design - design robustness directly determines build speed and test quality.
• Translate architecture into implementation plans - break down into assignable streams for Developer and Associate.
• Own day-to-day technical decisions during build when the Architect is focused on other projects.
• Identify architectural risks early and escalate before they become build or production problems.
• Build complex solution components end-to-end on AWS AgentCore and LangGraph - hands-on coding role.
• Scale solutions from POC to production: performance, reliability, monitoring, and cost management.
• Debug production failures: hallucination patterns, retrieval degradation, agent loops, latency regressions.
• Use AI coding tools (Claude Code, GitHub Copilot, Cursor, Cline) to accelerate delivery. Own all generated code.
• Build Low Code automations (Copilot Studio, Power Automate) when use case and bandwidth allow.
• Guide Developer and Associate through implementation, code reviews, and debugging.
• Ensure the team uses AI tools effectively - accelerating delivery without sacrificing code understanding.
• Work Mode: Hybrid - 3 days from office.
• Shift Timing: 1pm IST to 10pm IST

About You:

• Experience - 3-5 years total; 2-4 years production GenAI/LLM; 12-24 months multi-agent LangGraph; 3+ systems owned post-deployment.
• LangGraph - multi-agent state machines, parallel execution, checkpointing, HITL - non-negotiable
• AWS Bedrock - model deployment, knowledge bases, guardrails.
• Database & AI Data Access - SQL proficiency, NL-to-SQL, LLM-powered query layers. Snowflake a plus.
• Systems Integration - REST API development, MCP awareness, enterprise system connectors.
• Advanced RAG - hybrid search, re-ranking, query reformulation, retrieval evaluation.
• Evaluation Frameworks - RAGAS / TruLens, golden test sets, automated regression pipelines.
• Observability - LangSmith or LangFuse - agent tracing, production debugging.
• Python - expert-level - design patterns, async, testing, CI/CD.
• Multi-Model - OpenAI, Claude, Gemini, Llama - trade-offs at production scale.
• Pro Code vs Low Code - working knowledge of Copilot Studio and Power Automate; build when use case fits.
• AI Development Tools - Claude Code, GitHub Copilot, Cursor, or Cline - accelerate delivery; own and fix all generated code.
• Stakeholder Communication - demo AI solutions to business stakeholders; translate SME knowledge into requirements.
• AWS AgentCore Deep - all services hands-on.
• MCP / A2A - server/client production implementation.
• Document Intelligence - OCR, layout-aware chunking.
• Fine-Tuning - LoRA / QLoRA for domain adaptation.
• Certifications - AWS ML Specialty, Azure AI Engineer, GCP ML Engineer.