Agentic AI Software Engineer

Role & responsibilities

a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; }

AI Engineer (Python)

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Python.
• Build scalable APIs and microservices using FastAPI.
• Develop Agentic AI solutions and Multi-Agent workflows using frameworks such as LangGraph.
• Implement tool calling, agent orchestration, and external system integrations.
• Design and optimize prompts for LLM-based applications.
• Perform LLM evaluation, benchmarking, and performance monitoring.
• Develop workflow automation solutions leveraging AI capabilities.
• Design and integrate REST APIs and enterprise services.
• Deploy and manage AI solutions on AWS cloud platforms.
• Utilize Terraform for infrastructure provisioning and management.
• Collaborate with cross-functional teams to define and implement AI solution architectures.
• Follow best practices for security, scalability, observability, and maintainability.

Required Skills

• Strong proficiency in Python.
• Experience with FastAPI and REST API development.
• Knowledge of Agentic AI and Multi-Agent frameworks (LangGraph).
• Hands-on experience with Tool Calling and AI Agent Integration.
• Prompt Engineering for Generative AI applications.
• LLM Evaluation and Benchmarking techniques.
• AWS Cloud Services.
• Terraform (Infrastructure as Code).
• AI Solution Architecture.
• Workflow Automation and System Integration.

Preferred Skills

• LangChain
• RAG (Retrieval-Augmented Generation)
• Vector Databases (FAISS, Chroma, Pinecone)
• Docker and Kubernetes
• CI/CD Pipelines
• Git/GitHub
• AI Observability and Monitoring
• MCP (Model Context Protocol)

Preferred candidate profile