Gen AI Engineer

Responsibilities:

• Design, develop, and deploy agentic AI solutions using deep agent frameworks such as LangChain and LangGraph.
• Build multi-agent workflows leveraging LLMs (e.g., Claude via Amazon Bedrock) for reasoning, orchestration, and task execution.
• Develop robust Python-based services and pipelines for Generative AI and AI-driven automation use cases.
• Integrate AI agents with AWS data services including Glue, Athena, and S3 for data retrieval, processing, and analytics.
• Implement Retrieval-Augmented Generation (RAG) and tool-enabled agent architectures.
• Ensure solutions are scalable, secure, auditable, and production-ready.
• Collaborate with data platform and product teams to translate business problems into agent-based AI architectures.
• Contribute to architectural decisions, technical standards, and reusable frameworks for GenAI ecosystems.
• Support model governance, prompt versioning, observability, and performance optimization.

Required Qualifications:

• Strong proficiency in Python with experience building enterprise-grade applications.
• Experience developing APIs, microservices, and backend services for AI workloads.
• Solid understanding of object-oriented programming, asynchronous processing, and modular architectures.
• Hands-on experience with LangChain, LangGraph, and deep agent frameworks.
• Experience building autonomous agents, multi-agent systems, and stateful/event-driven workflows.
• Strong knowledge of Generative AI concepts including prompt engineering, chain-of-thought reasoning, tool-augmented LLMs, and RAG patterns.
• Practical experience working with Claude models via Amazon Bedrock.
• Familiarity with hallucination mitigation, evaluation techniques, and response quality control.
• Strong experience with AWS services including Amazon Bedrock, AWS Glue, Amazon Athena, and Amazon S3.
• Understanding of cloud security, IAM, logging, and cost optimization for AI workloads.

Agentic AI Expertise:

• Experience building AI agents from scratch, not just consuming APIs.
• Ability to design agents with goal-driven reasoning, tool usage, memory, and state management.
• Experience implementing multi-step task decomposition and agent orchestration.
• Experience designing multi-agent collaboration systems.
• Ability to integrate agents with APIs, databases, and enterprise data sources.
• Familiarity with agent observability, failure handling, and explainability.
• Ability to translate business workflows into agent-based execution models.

Preferred Skills:

• Experience with scalable AI architecture and distributed systems.
• Knowledge of monitoring, logging, and performance tuning for AI systems.
• Strong problem-solving and analytical thinking skills.
• Excellent communication and collaboration abilities.