AWS Lambda, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Automation, Cloud Computing, Continuous Deployment/Delivery, Continuous Integration, Docker, Error Handling, Git, JSON, Node.js, Python Programming/Scripting Language, REST (Representational State Transfer), React.js, Semantic Reasoner, Standards Development
Job Responsibilities:
Design, develop, and support cloud-native automation and Al agent workflows using Python and LLM orchestration frameworks (LangChain / LangGraph), deployed on AWS using containerized architectures.
• Develop automation solutions using Python.
• Build Al agents using LangChain and LangGraph to orchestrate tools, APls, and workflows.
• Integrate automations with enterprise systems via REST APIs and databases.
• Containerize services using Docker and support CI/CD pipelines.
• Deploy and operate solutions on AWS (IAM, S3, Lambda, ECS/Fargate, CloudWatch).
• Reasoning Engines: Experience with frontier models like GPT-4o, Claude 3.5, and Llama 3.x/4 specifically for tool-calling and JSON-mode outputs
Azure OpenAI proficiency .
• Agentic RAG 2.0: Develop "iterative retrieval" systems where agents autonomously decide if they have enough information or if they need to perform additional searches/queries.
• Implement logging, error handling, and basic monitoring.
• Collaborate with onshore architects and follow defined architecture standards.
Must Have skills:
Python (automation, backend services).
• JavaScript (React/Node JS)
• LangChain and/or LangGraph hands-on experience.
• Docker and container-based deployments.
• AWS Cloud Practitioner-level knowledge with hands-on exposure.
• REST APIS, JSON, Git.