Noida, Uttar PradeshPune, Maharashtra
Job Summary
Working under the guidance of the Generative AI Architect, the developer will translate architectural decisions into production-grade implementations, uplift team capabilities through training and mentorship, and independently drive the development of complex GenAI and Agentic AI features for enterprise-grade solutions.
Key Responsibilities
Act as the squad's embedded GenAI expert and single point of contact for all AI/GenAI-related decisions, implementation, and guidance.
Work under the GenAI Architect to interpret architectural blueprints and implement complex GenAI components, ensuring alignment with enterprise standards.
Integrate Large Language Models (LLMs) — including OpenAI, Azure OpenAI, Hugging Face, Anthropic, and Cohere — into enterprise workflows and products.
Design and implement Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration systems, and Agentic AI flows.
Build, maintain, and evolve APIs, automation scripts, and AI pipelines on the AIForce platform.
Train and mentor squad members (backend, frontend, full-stack developers) on GenAI concepts, tools, frameworks, and best practices — enabling the broader team to actively contribute to AI feature development.
Conduct LLM performance evaluation, prompt optimization, and model fine-tuning as required.
Champion Secure AI, AI governance, and responsible AI development practices across the squad.
Monitor, test, and troubleshoot deployed GenAI models and services in production environments.
Stay current with emerging GenAI frameworks, LLM advances, and industry trends; proactively assess and introduce relevant innovations.
Skill Requirements
Proven hands-on experience with Agentic AI and GenAI frameworks: LangChain, LlamaIndex, Hugging Face Transformers, AutoGen, CrewAI, or similar.
Demonstrated experience designing and implementing RAG architectures, vector search pipelines, and multi-agent systems.
Familiarity with LLM
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