01Overview
About the job
We are seeking an experienced AI Engineer to design and build production-grade Generative AI solutions with a strong focus on agentic workflows, multi-agent systems, and enterprise AI applications. The ideal candidate combines strong software engineering fundamentals with hands-on expertise in LLMs, RAG architectures, and AI agent frameworks.
Responsibilities
Design, architect, and develop scalable Generative AI applications and agentic solutions for real-world business use cases
Build and orchestrate AI agents using frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, Microsoft Copilot Studio, or similar technologies
Develop and maintain backend services, APIs, microservices, and data pipelines that power AI-driven products
Implement advanced AI patterns including RAG, Agentic RAG, tool/function calling, planning & reflection loops, and human-in-the-loop workflows
Engineer and optimize prompts, system instructions, and agent workflows to improve reliability, accuracy, and user experience
Integrate LLMs with enterprise systems, third-party APIs, vector databases, and knowledge repositories
Monitor, evaluate, and continuously improve model and agent performance using observability tools, metrics, and user feedback
Collaborate closely with Product, Engineering, Data, and Design teams to deliver impactful AI solutions
Stay current with emerging AI technologies, frameworks, and best practices, contributing innovative ideas to the team
Document architectures, design decisions, and reusable solution patterns while supporting knowledge sharing across teams
Requirements
5-7 years of experience in software engineering
Hands-on experience building applications using Generative AI and LLM technologies
Strong proficiency in Python and experience developing production-ready applications
Hands-on experience with at least two agentic AI frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot extensibility
Experience with cloud AI platforms including Azure OpenAI, AWS Bedrock, or Google Vertex AI/ADK
Strong backend development skills, including REST/gRPC APIs, asynchronous programming, Docker, and frameworks such as FastAPI or Flask
Solid understanding of leading LLMs including OpenAI GPT models, Anthropic Claude, Google Gemini, and open-source alternatives
Practical experience building RAG solutions using vector databases such as Pinecone, Weaviate, ChromaDB, or Qdrant
Expertise in prompt engineering, LLM orchestration, structured outputs, guardrails, ReAct patterns, and evaluation techniques
Strong problem-solving, system design, and architectural decision-making skills
Excellent communication skills with the ability to collaborate effectively across global teams
