Python Gen AI Engineer

Cognizant; Chennai District; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Cognizant is seeking engineers in India to advance AI agent frameworks with production-grade software. You will design modular architectures, integrate LangChain/LangGraph, and apply solid SDLC practices across CI/CD and testing, while ensuring governance and observability of AI systems.

The role emphasizes scalable API design, microservices, and reusable SDK development, with a focus on auditability, guardrails, and human oversight in AI workflows.

Qualifications

• Strong Python experience with production-grade software.
• Hands-on experience with agentic frameworks such as LangChain and LangGraph.
• Solid understanding of LLM fundamentals: prompting, tool calling, embeddings, memory systems.
• Experience designing modular, platform-agnostic architectures.
• Knowledge of SDLC processes (CI/CD, version control, testing).
• Experience with API design, microservices, and building reusable SDKs.

Skills

Python

LangChain

LangGraph

LLM fundamentals

Modular architecture

CI/CD

API design

Observability tooling

Governance concepts

Tools

LangSmith

Tracing frameworks

Eval harnesses

Job description

• Strong proficiency in Python, with hands-on experience building production-grade software (not just notebooks/prototypes).
• Practical experience with agentic frameworks such as LangChain, LangGraph, or similar.
• Solid understanding of LLM fundamentals — prompting, tool/function calling, RAG, embeddings, context management, memory systems.
• Experience designing modular, platform-agnostic architectures (i.e., not tightly coupled to a single LLM vendor or cloud provider).
• Understanding of SDLC processes (CI/CD, version control, code review, testing) and how AI agents can augment or automate them.
• Experience with API design, microservices, and building extensible/reusable frameworks or SDKs.
• Familiarity with agent evaluation and observability tooling (e.g., LangSmith, tracing frameworks, custom eval harnesses).
• Strong grasp of governance concepts for AI systems — guardrails, access control, auditability, human oversight.