Python & Java Full Stack Developer (AI-Capabilities)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Python & Java Full Stack Developer (AI-Capabilities) based in the United States.

This is a senior full-stack engineering opportunity focused on building AI-enabled platforms with direct, real-world impact in manufacturing environments. You will own features end to end, spanning AWS infrastructure, Python and Java services, agentic LLM workflows, and modern Angular applications. AI coding agents are an important part of the engineering workflow, but strong fundamentals, critical thinking, and rigorous validation remain essential. You’ll work across event-driven architectures, cloud-native services, data pipelines, and retrieval systems. The role offers significant technical ownership within a large-scale, multi-repository engineering environment. You’ll help shape reliable AI capabilities while contributing to systems where correctness, observability, and production resilience matter.

Accountabilities

• Design, develop, test, and deploy end-to-end features spanning AWS infrastructure, Python and Java backend services, agentic LLM workflows, and Angular/TypeScript frontends.
• Build and evolve AI workflows using Amazon Bedrock, including function and tool calling, RAG, embeddings, prompt design, validation loops, and production fallback strategies.
• Develop and maintain Python serverless services using AWS Lambda and Java microservices using Spring Boot or Quarkus, with REST APIs, event-driven integrations, persistence, asynchronous processing, and message-bus connectivity.
• Design resilient distributed systems with appropriate idempotency, retry, dead-letter, and failure-handling mechanisms.
• Define and maintain infrastructure as code using AWS CDK across multi-stack deployments and cross-stack dependencies.
• Design and maintain production API contracts, shared schemas, and interfaces while preserving backward compatibility across services and clients.
• Develop retrieval and scoring capabilities using log chunking, embeddings, semantic/vector search, OpenSearch, and relevance-ranking techniques.
• Build operational visibility through CloudWatch dashboards, alarms, tracing, structured diagnostic events, and other observability practices.
• Own and improve CI/CD workflows using Azure DevOps, including gated, reversible, blue/green, canary, and rollback deployment strategies.
• Contribute to shared foundational code while keeping high-impact changes narrowly scoped, well-tested, secure, and maintainable.
• Use AI coding agents thoughtfully by defining precise requirements, providing appropriate context, reviewing generated code critically, and validating behavior through testing and observability.

Requirements

• Bachelor’s degree in Computer Engineering, Computer Science, or a related discipline; a master’s degree is preferred.
• 10+ years of professional software development experience, ideally working with enterprise server, storage, networking, or similarly complex technology products.
• Strong Python development skills, including modern typing, asynchronous programming, data validation frameworks such as Pydantic, structured error handling, and maintainable large-scale code organization.
• Deep Java backend expertise with Spring Boot and/or Quarkus, clean architecture, strong use of the type system, and experience with modern concurrency concepts such as Java virtual threads.
• Extensive hands-on AWS experience, including Lambda, ECS Fargate, DynamoDB, S3, SQS, OpenSearch, VPC, VPC Endpoints, API Gateway, EventBridge, IAM, CloudWatch, SSM Parameter Store, ECR, and Amazon Bedrock.
• Strong persistence and data-engineering knowledge, including JPA/Hibernate, JDBC, transaction management, DynamoDB access patterns, relational database design, query optimization, and analytical data processing.
• Proven experience designing and operating microservices and event-driven architectures using technologies such as NATS, Kafka, SQS, or similar messaging platforms.
• Practical experience developing LLM-powered applications, including function calling, prompt engineering, RAG, embeddings, agent workflows, and systematic evaluation of AI-generated outputs.
• Experience building modern Angular/TypeScript frontends that consume production APIs.
• Familiarity with Docker, Docker Swarm and/or Kubernetes, Git, Azure DevOps pipelines, code review, and multi-repository development enviro…