Artificial Intelligence Engineer

Responsibilities

• Design, develop, and deploy enterprise-grade Agentic AI and Generative AI applications using LLMs, RAG pipelines, prompt engineering, and multi-agent frameworks.

• Build scalable AI-powered backend services and APIs using Python or Java/Spring Boot

  , integrating AI capabilities into enterprise applications.

• Develop intelligent workflows using Amazon Bedrock, OpenAI, LangChain/LangGraph

  , vector databases, and enterprise APIs.

• Build and optimize RAG solutions, AI agents, tool calling, prompt orchestration, and structured output pipelines.

• Develop REST APIs and microservices to integrate AI solutions with enterprise systems and business applications.

• Evaluate, fine-tune, test, and optimize LLM performance while implementing AI guardrails and responsible AI practices.

• Collaborate with product owners, architects, and engineering teams to deliver scalable, production-ready AI solutions.

• Mentor developers on AI best practices and contribute to the adoption of AI across enterprise applications.

Required Skills

• Strong hands-on experience with Agentic AI, Generative AI, LLMs, RAG, Prompt Engineering, and AI Agents

• Experience with Amazon Bedrock, OpenAI APIs, LangChain/LangGraph

  , MCP, or similar AI frameworks

• Strong programming experience in Python and/or Java with Spring Boot

• Experience building REST APIs

  , microservices, and integrating enterprise applications

• Experience with Vector Databases

  (Pinecone, Chroma, FAISS, Weaviate, or similar)

• Knowledge of Kafka or other event-driven messaging platforms is a plus

• Basic familiarity with AWS and Docker for deploying AI applications

• Experience with Git and CI/CD workflows

• Strong problem-solving, communication, and collaboration skills

Preferred

• Experience with AI evaluation frameworks, guardrails, model monitoring, and prompt optimization.

• Exposure to GraphRAG, Knowledge Graphs, or autonomous agent frameworks is a plus.