We are looking for a GenAI Engineer with hands-on experience in Generative AI and/or Agentic AI to design and develop enterprise-grade AI solutions. The role involves building LLM-powered applications, AI agents, RAG pipelines, and intelligent automation workflows. The ideal candidate should have strong Python development skills and experience with modern LLM/agent frameworks. You will work closely with product and engineering teams to take GenAI use cases from prototype to production.

Roles & Responsibilities

- Design, develop, and deploy Generative AI and Agentic AI applications using LLMs and modern AI frameworks.
- Build AI agents and multi-agent workflows with tool/function calling, reasoning, planning, and orchestration.
- Develop RAG-based solutions including document ingestion, chunking, embeddings, retrieval, and vector search.
- Integrate LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or equivalent models into enterprise applications.
- Develop and integrate LLM tools, APIs, and external services to enable agent-driven workflows.
- Implement prompt engineering, context management, structured outputs, and guardrails.
- Build scalable Python-based APIs and backend services for GenAI applications.
- Evaluate and optimize LLM applications for accuracy, latency, cost, reliability, and hallucination reduction.
- Implement observability and evaluation using tools such as LangSmith, MLflow, or equivalent.
- Collaborate with product, engineering, and business teams to translate use cases into production-ready AI solutions.




- Deploy GenAI solutions using cloud, Docker, CI/CD, and modern software engineering practices.

Requirements

- Mandatory hands-on experience in Generative AI or Agentic AI development.
- Strong programming experience in Python.
- Hands-on experience with LLMs and LLM application development.
- Experience with LangChain, LangGraph, AutoGen, CrewAI, or similar agent frameworks.
- Strong understanding of RAG architecture, embeddings, vector databases, and semantic search.
- Experience with AI agents, tool/function calling, agent orchestration, and multi-step workflows.
- Strong knowledge of prompt engineering and LLM context management.
- Experience integrating LLM APIs and third-party APIs/services.
- Experience developing REST APIs and production-grade backend services.
- Understanding of LLM evaluation, hallucination mitigation, guardrails, and responsible AI practices.
- Experience with at least one cloud platform AWS, Azure, or GCP.
- Good understanding of Git, Docker, CI/CD, testing, and software engineering best practices.

Valuable to Have

- Experience with multi-agent systems.
- Experience with MCP (Model Context Protocol).
- Experience with fine-tuning / LoRA / model customization.
- Experience with Azure AI / AWS Bedrock / Google Vertex AI.
- Experience with Pinecone, FAISS, Weaviate, Chroma, Milvus, or similar vector databases.
- Experience with LLM observability and evaluation frameworks.
- Experience building enterprise GenAI solutions in production.

📌 GenAI Engineer (Noida)
🏢 IRIS SOFTWARE
📍 Noida