Agentic AI Developer

Role Summary Develop, test, and deploy AI agents that automate regulated and semi-regulated business processes using AWS Bedrock. Build and maintain document-processing pipelines that extract structured information from enterprise documents and integrate it into AI-driven workflows, helping replace manual processes with intelligent automation. Key Responsibilities Agent Development Develop AI agents on AWS Bedrock (Amazon Nova and other foundation models) for document generation, data validation, and case intake use cases. Implement business logic using AWS Fargate following established service patterns (e.g., email-triggered and chatbot-triggered workflows). Integrate AI services with Microsoft Graph API for Microsoft Teams messaging, file handling, and delivery of agent outputs. Develop and maintain prompts, agent configurations, and guardrails to ensure reliable and compliant AI behavior. Perform unit and integration testing to validate agent accuracy, performance, and response quality. Troubleshoot, optimize, and enhance AI agent workflows based on testing results and user feedback. Collaborate with solution architects, QA teams, and business stakeholders to deliver production-ready AI solutions. Document Processing Develop and maintain document-processing services using AWS Fargate. Build extraction pipelines for structured and semi-structured documents using OCR and Intelligent Document Processing (IDP) technologies. Integrate third-party document extraction tools into AI workflows. Support validation and quality improvements of extracted data to meet business and audit requirements. Optimize document extraction accuracy through testing and continuous improvements. Assist in deploying document-processing services into production environments. Required Experience 3–5 years of software development experience, with at least 1–2 years developing Generative AI or LLM-based applications. Hands-on experience with Python and REST API development. Working knowledge of AWS services, preferably AWS Bedrock, Lambda, ECS/Fargate, SQS, SNS, or similar cloud-native services. Experience with prompt engineering, Retrieval-Augmented Generation (RAG), AI agent frameworks, or LLM orchestration tools. Experience building integrations using APIs such as Microsoft Graph API or similar enterprise platforms. 2+ years of experience with document processing, OCR, or Intelligent Document Processing solutions such as AWS Textract, Azure Document Intelligence, or equivalent. Familiarity with event-driven application architecture and microservices. Experience using Git, CI/CD pipelines, and Agile development methodologies. Preferred Qualifications Experience with financial services, insurance, healthcare, or other regulated industries. Familiarity with AI evaluation, prompt optimization, and model monitoring. Exposure to vector databases and semantic search technologies. Understanding of AI governance, responsible AI principles, and security best practices. Experience working with Docker and containerized applications. Exposure to enterprise chatbot or conversational AI solutions. Key Competencies Strong analytical and problem-solving skills. Ability to build scalable and maintainable AI solutions. Effective collaboration and communication skills. Attention to quality, security, and compliance. Continuous learning mindset with interest in emerging AI technologies.