GenAI- Senior Software Engineer

Role Overview

We are looking for a hands-on AI Engineer to design, develop, and deploy AI-powered applications leveraging LLMs, Agentic AI frameworks, and modern AI engineering tools. The ideal candidate should have practical experience building AI agents, copilots, and RAG-based solutions that solve real business problems and create measurable value.
Key Responsibilities

1. Design and develop AI agents, copilots, and autonomous workflows.
2. Build solutions using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and Google ADK.
3. Develop RAG solutions, semantic search capabilities, and enterprise knowledge assistants.
4. Integrate AI solutions with business applications, APIs, databases, and enterprise systems.
5. Leverage AI-assisted development tools such as Claude Code, Cursor, and GitHub Copilot.
6. Package, deploy, and monitor AI applications in cloud environments.
7. Contribute reusable frameworks, accelerators, and AI engineering best practices.

Required Technical Skills

Programming & Engineering

1. Strong proficiency in Python.
2. Experience with REST APIs and integrations.
3. FastAPI, Flask, or similar frameworks.
4. Strong software engineering and system design fundamentals.

Agentic AI & LLMs

1. Hands-on experience with one or more:
2. LangChain
3. LangGraph
4. CrewAI
5. AutoGen
6. Google ADK
7. Prompt Engineering
8. Function/Tool Calling
9. Agent Workflows and Memory Concepts
10. Building LLM-powered applications

RAG & Knowledge Systems

1. Retrieval-Augmented Generation (RAG)
2. Vector Databases (Pinecone, Chroma, Weaviate, Milvus, etc.)
3. Semantic Search and Embeddings

Cloud & Deployment

1. Docker
2. Azure, AWS, or GCP
3. CI/CD fundamentals

Preferred Skills

1. Model Context Protocol (MCP)
2. Multi-Agent Systems
3. GraphRAG
4. Semantic Kernel
5. OpenAI Agents SDK
6. PydanticAI
7. AI Evaluation Frameworks (Promptfoo, RAGAS)
8. Knowledge Graphs
9. React or Streamlit-based AI applications

Professional Attributes (Mandatory)

1. Strong collaborator capable of working effectively across engineering, product, business, and leadership teams.
2. Excellent communication skills with the ability to explain technical concepts to diverse audiences.
3. Confident, proactive, and self-driven individual who takes ownership and delivers results.
4. Strong networking and relationship-building abilities, with the capability to engage stakeholders across teams and geographies.
5. Comfortable conducting demos, presentations, workshops, and technical discussions.
6. Passionate about continuous learning and staying current with emerging AI technologies.

Experience Requirements

1. 3–8 years of overall software engineering experience.
2. Minimum 2 years of hands-on experience in Generative AI, Agentic AI, or LLM-based application development.
3. Experience building and delivering AI-powered applications, agents, copilots, or automation solutions in enterprise or production environments.