Generative Ai

Role & responsibilities

Description
Hire Type: CWR
Experience: 1215 years of IT experience, with end-to-end implementation expertise in Gen AI, LLM, RAG, Agentic AI, prompt engineering, Langchain, Langgraph
Location: Chennai/Bangalore
Notice: Immediate Joiners

JD for this requirement:

Responsibilities

• Architect and build enterprise-grade Generative AI applications combining LLMs, retrieval, structured data, orchestration, and workflow automation.
• Design agentic systems and multi-step reasoning workflows using LangGraph or equivalent with clear control over state, memory, tool invocation,  and human-in-the-loop checkpoints.
• Build fault-tolerant orchestration for long-running AI workflows using Temporal or similar platforms.
• Drive reference architectures for model routing, prompt versioning, observability, experimentation, and safe production rollout.
• Establish LLM/agent evaluation frameworks — offline evals, regression suites, trace diagnostics, and quality metrics tied to business outcomes.
• Own full feature development across design, implementation, testing, shipping, and servicing.
• Write and review clean, high-quality code with a focus on performance, scalability, and maintainability.
• Set best practices for AI tooling, service observability, alerting, and incident response.
• Mentor engineers across the team and foster a culture of technical excellence and continuous learning.
• Use AI tools in your daily workflow and advocate evolving best practices to the broader team.

Required Qualifications

• 15+ years of experience building large-scale distributed systems, platforms, or enterprise applications.
• Proven track record shipping production AI/LLM-powered applications — agentic workflows, RAG systems, or intelligent automation.
• Deep expertise in Generative AI: LLMs (OpenAI), Prompt Engineering, RAG, vector search, and AI agent orchestration.
• Hands-on experience with agent frameworks**: LangChain, LangGraph, AutoGen,** or equivalent.
• Frontend and backend background to integrate AI solutions end-to-end into existing applications.
• Strong software engineering fundamentals: system design, algorithms, testing, debugging, and code review.
• Demonstrated ability to lead technical direction and mentor engineers.
• Comfort in ambiguous, fast-moving problem spaces where best practices are still emerging.
• Bachelor/Masters in Computer Science, Engineering, or equivalent practical experience.

Preferred Qualifications

• Experience with additional AI frameworks: Semantic Kernel, LlamaIndex, or similar.
• Hands-on experience with AI developer tooling: GitHub Copilot, Claude Code, OpenAI Codex, or Cursor.
• Familiarity with agentic patterns — multi-step reasoning, tool/function calling, RAG, and human-in-the-loop workflows.
• Background in developer tooling, build systems, CI/CD pipelines, or engineering systems at scale.
• Experience with workflow orchestration platforms such as Temporal.