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 explicit 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.

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