How will you make an impact?- As the Python & Java Full Stack Developer (AI-Assisted), you will build AI-assisted platforms for manufacturing tests and debug automation software with direct, real-world consequences on the factory floor.
- You will own end-to-end features across event-driven platforms, from cloud infrastructure and backend microservices, up through an agentic LLM pipeline, out to a modern web frontend.
- LLMs are a core building block of what we build, and AI coding agents are a core part of how we build it but we treat them as power tools operated by strong engineers, not autopilots.
- This role requires someone who can define work with precision, critically evaluate agent-generated output, and write code themselves when needed.
- As the Python & Java Full Stack Developer (AI-Assisted), you are equally comfortable writing a Python Lambda handler, designing an agent tool, building a Java microservice, defining infrastructure as code, tuning a message-bus consumer, and building an Angular component with an AI agent working alongside you.
How We Work with AI- We use AI coding agents Claude, Kiro, and similar agentic IDEs/CLIs (we use Kiro) but as power tools in the hands of engineers who could do the work without them.
- We are seeking a passionate developer who has experienced building without AI, understands its capabilities and limitations, and knows when to rely on AI versus writing code themselves.
- The challenge isn't generating code. It's defining requirements precisely and rigorously validating the output.
Engineering Fundamentals- You can read, debug, and correct generated code as readily as you can produce it, and you can justify an architectural decision independent of what any tool suggested.
Spec-Driven Development- Decompose features into clear requirements, design, and task breakdowns that both humans and agents execute against, treating the spec as the source of truth and iterating on it.
Skills and Powers- Author and use reusable agent capabilities (skills, steering docs, custom tools/MCP integrations, project conventions) to encode team standards and make agents productive in a large codebase.
Prompt and Context Engineering- Give agents the right context (conventions, contracts, constraints) and validate their output rather than trusting it blindly.
Correctness Discipline- Pair agent velocity with strong testing, review, and observability so fast-moving changes stay safe in production.
What will you do? - Design, build, and ship feature end-to-end across the full stack AWS infrastructure, Python and Java backend services, agentic LLM workflows, and the Angular frontend for a system serving manufacturing across multiple sites.
- Build and evolve agentic AI workflows on Amazon Bedrock.
(LLM reasoning + embeddings): - tool/function calling, RAG,
- prompts,
- validation loops, and
- fallback strategies that stay correct and observable under production load
- Own backend services across two ecosystems
- Python serverless (Lambda, event-driven) and
- Java microservices (Spring Boot/Quarkus) with REST and event-driven APIs, persistence, async pipelines, and message-bus integrations
- Care for idempotency, retries, and dead-letter handling throughout
- Define and evolve infrastructure as code (AWS CDK) across multi-stack deployments with cross-stack references.
- Treat published API surfaces as backwards-compatibility contracts, using shared interface/schema libraries consumed across services and clients.
- Develop retrieval and scoring logic:
- log chunking, embeddings, vector/semantic search in OpenSearch, and relevance ranking
- Instrument with CloudWatch dashboards, alarms, tracing, structured diagnostic events and own CI/CD on Azure DevOps with gated, reversible rollouts.
- Contribute to shared foundational code with wide blast radius, keeping changes narrow and well-tested.
How will you get here? Python- Modern typing, async patterns, data validation (e.g., Pydantic), clean error handling, and a codebase-scale sense of structure.
Backend Engineering in Java- Deep experience with Spring Boot and/or Quarkus, clean architecture, and idiomatic use of the type system.
- Production AWS serverless and cloud experience across the stack:
ComputeData & MessagingNetworking- VPC
- VPC Endpoints
- API Gateway (Private)
Eventing & SchedulingSecurity & Identity- IAM
- IAM Roles Anywhere (trust anchor, cross-environment access)
AIOps & Config- CloudWatch (alarms + dashboards)
- SSM Parameter Store
- ECR assets
Persistence Expertise- JPA / Hibernate
- JDBC
- transaction management
- NoSQL data modeling (DynamoDB access patterns),
- and relational database design, management, and query optimization
API Design- Production REST services; comfortable with versioning and backwards-compatibility.
Modern Concurrency- Java virtual threads (Project Loom) and reasoning clearly about concurrency correctness.
Microservices & Event-Driven Architecture- Designing and operating microservices with a message bus (NATS.io, Kafka, SQS, or similar), including idempotency, retries, and failure handling.
Hands-on LLM/agent Development- Building applications with LLMs (function calling, prompt design, RAG, embeddings) and evaluating output quality. You understand that specifying and validating agent behavior is the hard part.
AI-assisted development Practice- Daily, judicious use of AI coding agents (Claude, Kiro, etc.), spec-driven workflows, and reusable agent skills/powers, paired with the fundamentals to review their output critically.
Frontend Development in Angular- Building and maintaining a modern web UI (Angular/TypeScript) that consumes these APIs.
Testing Discipline- Unit, integration, and mocking as a first-class part of shipping.
Containerization & Orchestration- Docker and Docker Swarm
- Kubernetes
Cloud-Native Workflow- Git
- Azure DevOps pipelines
- and code review in a sizable multi-repo codebase
Deployment Strategies- Blue/green, canary, gated rollout, and rollback
Observability, Security & Analytics- Structured logging, tracing, metrics; secure coding and auth fundamentals; and building/consuming analytics on operational data
Education:- BS degree in Computer Engineering, Computer Science or related field
- MS preferred
Experience: - 10+ years' experience in a software development capacity with enterprise server, storage or networking products.
What Can Jabil Offer You?Along with growth, stability, and the opportunity to be challenged, Jabil offers a competitive benefits package that includes:
- Medical, Dental, Prescription Drug, and Vision Insurance with HRA and HSA options
- 401K Match
- Employee Stock Purchase Plan
- Paid Time Off
- Tuition Reimbursement
- Life, AD&D, and Disability Insurance
- Commuter Benefits
- Employee Assistance Program
- Pet Insurance
- Adoption Assistance
- Annual Merit Increases
- Community Volunteer Opportunities
The pay range for this role is $100,100 - $180,200. Job-related, non-discriminatory factors used to determine the actual offered rate include qualifications and experience, geographic location, education, external market data, and consideration of internal equity. The anticipated close date of this job requisition is: October 04, 2026.
As part of the total rewards package, this position is eligible for a short-term incentive based on performance. In addition, Jabil offers benefits to enhance your health, wealth, and resilient self. These include medical, dental, and vision insurance plans; paid time off accruing at a rate of 3.07 hours during your first year of employment; 4 weeks of paid parental leave; in 2027, 11 company-paid holidays (9 fixed holidays and 2 optional floating holidays), subject to change yearly; 401(k) retirement plan; and employee stock purchase plan.
