AI Engineer

We are looking for an experienced AI Engineer to design, develop, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents. The ideal candidate should have strong expertise in Python, FastAPI, AWS, and Amazon Bedrock, with hands-on experience in building scalable, production-ready AI applications.

Responsibilities:

• Design, develop, and deploy AI/LLM-powered applications and AI agents.
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Develop scalable backend services and REST APIs using Python and FastAPI.
• Implement semantic search, hybrid search, embeddings, reranking, and retrieval optimization.
• Integrate foundation models such as GPT, Claude, Llama, Gemini, and Amazon Nova.
• Build multi-agent workflows using LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
• Implement prompt engineering, structured outputs, and LLM evaluation workflows.
• Work with AWS services, including Amazon Bedrock, S3 OpenSearch, Lambda, ECS/EKS, and related cloud technologies.
• Optimize AI applications for scalability, performance, latency, and cost.
• Implement AI observability, guardrails, hallucination mitigation, and monitoring.
• Collaborate with engineering and DevOps teams to deploy production-ready AI solutions.

Requirements:

• 6+ years of software development experience.
• Strong proficiency in Python and FastAPI.
• Hands-on experience with AI/LLM applications, RAG pipelines, and AI agents.
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.
• Experience with MCP (Model Context Protocol) server and client integrations.
• Expertise in vector databases such as Pinecone, ChromaDB, Qdrant, or Weaviate.
• Strong understanding of embeddings, semantic search, hybrid search, BM25 and reranking.
• Experience with prompt engineering, tool calling, and structured outputs.
• Hands-on experience with GPT, Claude, Llama, Gemini, Amazon Nova, or similar foundation models.
• Mandatory experience with AWS and Amazon Bedrock.
• Strong knowledge of SQL, Git, GitHub, REST APIs, authentication, and secure AI application development.
• Preferred Skills: Docker and Kubernetes, LangSmith, Langfuse, Arize Phoenix, Helicone, Ragas, DeepEval, Node.js / TypeScript, MLOps / LLMOps, Terraform / CloudFormation.
• Experience deploying enterprise-scale AI solutions on AWS.