AI Developer

Overview This role supports the engineering, deployment, and operation of internal AI applications built on an established Python and Angular codebase and AWS-native architecture. The position is focused on production-quality full-stack software engineering and cloud deployment of AI-enabled applications rather than AI research or experimentation. Responsibilities The ideal candidate is a strong full-stack software developer with professional experience in Python back-end development and Angular front-end development, along with hands-on experience working in Git-based development environments, AWS CI/CD pipelines, Infrastructure as Code (Terraform), and multi-environment AWS deployments. This individual should be capable of independently developing, testing, reviewing, deploying, and troubleshooting complete application features across the front end, APIs, back-end services, and AWS infrastructure throughout the software development lifecycle. AI-assisted development tools may be used to improve productivity; however, the developer is expected to understand, validate, test, and take ownership of all code they produce. The successful candidate must be able to independently reason through software architecture, application logic, deployment issues, and production failures rather than relying primarily on AI-generated code. Technical Responsibilities Develop, maintain, debug, and enhance production-quality Python applications and AI services within an established internal codebase Work effectively within Git-based development workflows, including branching strategies, pull requests, merge conflict resolution, code reviews, and release management Build, maintain, and troubleshoot CI/CD pipelines used to deploy applications across AWS development, staging, and production environments Understand and work within an AWS multi-account and multi-environment architecture, including IAM roles, policies, permissions, service accounts, and cross-service access Develop and maintain Infrastructure as Code using Terraform, including reviewing Terraform plans and troubleshooting infrastructure deployment failures Deploy and troubleshoot AWS-native applications using services such as Lambda, Step Functions, API Gateway, containers, Amazon Bedrock, and OpenSearch Diagnose deployment and operational issues across application code, CI/CD pipelines, AWS infrastructure, IAM permissions, networking, and service integrations Implement and extend Retrieval-Augmented Generation (RAG) and AI orchestration workflows using frameworks such as LangChain and LangGraph Develop and maintain APIs and data integration services supporting AI applications, structured metadata, and enterprise data sources Develop and maintain Angular-based web application interfaces, including components, services, routing, forms, state/data handling, validation, and integration with REST APIs and Python back-end services Implement end-to-end full-stack features spanning Angular/TypeScript user interfaces, API contracts, Python services, data access, authentication/authorization, and AWS-hosted application components Troubleshoot browser and front-end issues, API integration failures, application state and data-flow problems, and cross-layer defects between the Angular client and Python/AWS services Write maintainable, testable, and well-documented code consistent with established software engineering standards Perform peer code reviews and help establish and enforce coding, testing, source-control, and deployment standards Participate in Scrum-based development, sprint planning, backlog refinement, and technical estimation Translate business and non-developer feature requirements into clear technical designs and actionable development work items Support onboarding and mentoring of developers working within the organization's AI development framework and AWS environment Collaborate with cloud, cybersecurity, infrastructure, and operations teams to support secure and compliant application deployments Skills Required Required Technical Skills Strong professional Python software development experience, including object-oriented design, debugging, testing, dependency management, and working within established codebases Strong professional Angular and TypeScript development experience building and maintaining production web applications within established codebases Demonstrated full-stack development experience integrating Angular front ends with REST APIs and Python back-end services, including data models, validation, error handling, authentication/authorization, and end-to-end troubleshooting Strong working knowledge of modern web application fundamentals, including HTML, CSS, responsive UI development, client-side routing, asynchronous API communication, and browser-based debugging Experience writing and maintaining automated tests for both front-end and back-end application components Strong hands-on proficiency with Git and Git-based software development workflows, including branches, pull requests, merges, conflict resolution, tagging, and code reviews Demonstrated experience building, using, and troubleshooting CI/CD pipelines for automated application deployment Hands-on experience deploying and troubleshooting applications in AWS Working knowledge of AWS IAM, including roles, policies, permissions, and troubleshooting access-related deployment and runtime issues Hands-on experience with Infrastructure as Code, preferably Terraform Experience working with multiple application environments such as development, staging, and production Experience developing and integrating REST APIs and CRUD-based services Ability to independently troubleshoot issues spanning application code, deployment pipelines, cloud infrastructure, permissions, and service integrations Experience writing automated tests and validating code before deployment Experience using AI coding assistants as productivity tools while maintaining independent ownership and understanding of the resulting code Familiarity with Agile/Scrum software development practices AI-Specific Technical Skills Experience developing production applications using Large Language Models (LLMs) Hands-on experience with LangChain and/or LangGraph Experience implementing or supporting Retrieval-Augmented Generation (RAG) architectures Understanding of prompt engineering and structured LLM interactions Experience integrating applications with hosted LLM platforms; AWS Bedrock experience is strongly preferred Experience optimizing AI workflows for performance, reliability, accuracy, and cost Familiarity with vector search, embeddings, metadata filtering, and enterprise knowledge retrieval Preferred / Nice-to-Have AWS certification or significant equivalent hands-on AWS experience Experience with AWS Bedrock, OpenSearch, Lambda, Step Functions, API Gateway, and containerized workloads Advanced Terraform experience, including reusable modules, state management, and environment-specific deployments Experience designing or maintaining CI/CD pipelines and automated deployment processes Familiarity with AWS CloudWatch and application observability, logging, monitoring, and alerting Experience with metadata tagging, versioned knowledge sources, and access-aware retrieval, including RBAC and ABAC concepts Experience working in secure, regulated, or government cloud environments; AWS GovCloud experience is a plus Experience participating in technical design reviews, peer code reviews, or mentoring other developers Experience with additional front-end frameworks such as React or Blazor, component libraries/design systems, or advanced Angular architecture and p