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
- Design and develop AI agents, copilots, and autonomous workflows.
- Build solutions using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, and Google ADK.
- Develop RAG solutions, semantic search capabilities, and enterprise knowledge assistants.
- Integrate AI solutions with business applications, APIs, databases, and enterprise systems.
- Leverage AI-assisted development tools such as Claude Code, Cursor, and GitHub Copilot.
- Package, deploy, and monitor AI applications in cloud environments.
- Contribute reusable frameworks, accelerators, and AI engineering best practices.
Required Technical Skills
Programming & Engineering
- Strong proficiency in Python.
- Experience with REST APIs and integrations.
- FastAPI, Flask, or similar frameworks.
- Strong software engineering and system design fundamentals.
Agentic AI & LLMs
- Hands-on experience with one or more:
- LangChain
- LangGraph
- CrewAI
- AutoGen
- Google ADK
- Prompt Engineering
- Function/Tool Calling
- Agent Workflows and Memory Concepts
- Building LLM-powered applications
RAG & Knowledge Systems
- Retrieval-Augmented Generation (RAG)
- Vector Databases (Pinecone, Chroma, Weaviate, Milvus, etc.)
- Semantic Search and Embeddings
Cloud & Deployment
- Docker
- Azure, AWS, or GCP
- CI/CD fundamentals
Preferred Skills
- Model Context Protocol (MCP)
- Multi-Agent Systems
- GraphRAG
- Semantic Kernel
- OpenAI Agents SDK
- PydanticAI
- AI Evaluation Frameworks (Promptfoo, RAGAS)
- Knowledge Graphs
- React or Streamlit-based AI applications
Professional Attributes (Mandatory)
- Strong collaborator capable of working effectively across engineering, product, business, and leadership teams.
- Excellent communication skills with the ability to explain technical concepts to diverse audiences.
- Confident, proactive, and self-driven individual who takes ownership and delivers results.
- Strong networking and relationship-building abilities, with the capability to engage stakeholders across teams and geographies.
- Comfortable conducting demos, presentations, workshops, and technical discussions.
- Passionate about continuous learning and staying current with emerging AI technologies.
Experience Requirements
- 3–8 years of overall software engineering experience.
- Minimum 2 years of hands-on experience in Generative AI, Agentic AI, or LLM-based application development.
- Experience building and delivering AI-powered applications, agents, copilots, or automation solutions in enterprise or production environments.
Total Experience Expected: 02-04 years