AI Engineer

Roles & Responsibilities:

Design, build, and deploy AI/LLM-powered applications including chatbots, knowledge assistants, document AI, and multi-agent systems
Integrate with LLM providers such as Azure OpenAI, OpenAI, Anthropic Claude, Google Gemini, and Amazon Bedrock
Develop RAG pipelines, AI agents, and agentic workflows using LangChain, LangGraph, LlamaIndex, or similar frameworks
Build scalable Python backends using FastAPI with async programming and REST API design
Deploy and manage applications on Azure and AWS cloud infrastructure
Work with vector databases and implement semantic search and retrieval solutions
Set up and maintain CI/CD pipelines using GitHub Actions or Azure DevOps
Collaborate with cross-functional teams to translate business requirements into AI solutions

Required Skills:

2-4 years of hands-on experience building and shipping AI/LLM solutions in production
Strong Python expertise with FastAPI, async programming, and REST API development
Hands-on experience with at least two LLM providers Azure OpenAI, OpenAI, Anthropic Claude, Gemini, or Amazon Bedrock
Practical knowledge of RAG, prompt engineering, function calling, structured outputs, and AI agents
Experience with LLM frameworks LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, or AutoGen
Proficiency in vector databases such as Azure AI Search, pgvector, Pinecone, Qdrant, or Weaviate
Azure experience: Azure OpenAI, AI Foundry, AI Search, Document Intelligence, Functions, App Service, Key Vault, Blob Storage
AWS experience: Bedrock, ECS/EKS, Lambda, S3, RDS, API Gateway, CloudWatch, IAM
Hands-on with Docker, Kubernetes, and CI/CD pipelines
Must have independently built at least 3 of the following: AI Chatbot, Knowledge Assistant, Document AI/OCR, Email Automation, Ticket Classification, AI Copilot, AI Search, Workflow Automation, AI Agent, or Multi-Agent System

Good to Have:

Services