Java Full Stack Software Engineer Jobs in Indianapolis, IN

You lead software development projects end to end — scoping, technical design, delivery, and rollout — while writing production code across Ruby on Rails, React, and Java. You think in service boundaries, you raise the engineering bar around you, and you have made AI-assisted development a measurable advantage for your whole team, not just for yourself.

Ruby on Rails · Java · React · PostgreSQL · Node.js · Microservices · Metabase · REST/GraphQL APIs · GCP · Git · CI/CD · AI-assisted development

• Lead software development projects end to end — scoping, technical design, execution, rollout, and post-launch measurement
• Own the architecture and implementation of features spanning React front ends, Rails and Java services, and PostgreSQL
• Define service boundaries, API contracts, and data models across our microservice architecture
• Serve as the team's AI-enablement lead — establish the workflows, patterns, and guardrails for AI-assisted development, and teach mid-level and junior engineers to use them well
• Mentor mid-level and junior engineers through design reviews, pairing, and 1:1 guidance
• Set coding standards, review practices, and architectural patterns across the team
• Drive PostgreSQL optimization — query tuning, indexing, partitioning, connection pooling, replication
• Own technical risk assessment and mitigation for major feature releases
• Champion observability — logging, alerting, and monitoring best practices in GCP
• Collaborate with engineering leadership on roadmap planning and capacity estimation
• Evaluate and introduce new tools, libraries, and approaches with disciplined rigor
• Participate in the on-call rotation and lead incident response

• 6+ years building and shipping production software, including 2+ years as the technical owner of projects or a team
• A proven track record leading software development projects end to end — scoping, design, delivery, rollout, and accountability for the outcome. Be ready to walk us through two projects you led.
• Ruby on Rails in production — you have owned Rails services and their data models, not just contributed tickets to them
• React in production — component architecture, hooks, state management, and front-end testing. TypeScript strongly preferred.
• Java in production — modern Java with Spring or an equivalent framework, plus the build and test tooling around it
• Microservice frameworks and distributed systems — service decomposition, inter-service communication, caching, queuing, and consistency trade-offs. Strangler Fig migrations a major plus.
• A proven record of using AI/LLM development tools to increase throughput — and of teaching others to do the same. Come prepared to describe your workflow, what you measured, and how your team's output changed, not just your own.
• Sound judgment about AI-generated code — you can tell when it is wrong, when it introduces a security or performance problem, and when to throw it out entirely
• Strong PostgreSQL engineering — performance tuning, indexing, schema design, and migrations at scale; comfort with analytics and reporting pipelines (Metabase or similar)
• Strong API design — REST and GraphQL, versioning, and backward compatibility; production Node.js experience
• Hands-on GCP or equivalent cloud experience (IAM, Cloud Run, Pub/Sub, BigQuery), containerized services, and ownership of CI/CD pipelines
• Automated testing discipline and security-conscious engineering — OWASP, auth/authz patterns, and PCI DSS or comparable regulated-data experience

• Leads through influence — engineers look to you for patterns, not just answers
• Coaches deliberately — you measure your impact partly by how much better the engineers around you get
• Executive presence in technical conversations — you hold your own with product, design, and business stakeholders
• Constructive and direct — you give hard feedback kindly and receive it professionally
• Strategic thinker who balances long-term architecture with short-term delivery pressure
• Visible culture carrier — you model the engineering values you want the team to have

• Experience leading a team through a platform migration or re-architecture, especially monolith to microservices
• Experience introducing AI tooling at an organization — standards, guardrails, or a formal enablement program
• Experience in vertical SaaS or sports/fitness tech
• Contributions to technical strategy or engineering hiring
• Experience with payments or other regulated data domains

• A project-leadership deep dive on something you owned end to end — how you scoped it, what went wrong, and what you decided
• A practical working session with AI tools allowed and encouraged — we care whether the result is correct and whether you can defend every line of it

• A practical working session with AI tools allowed and encouraged — we care whether the result is correct and whether you can defend every line of it
• A system design conversation on service boundaries, API contracts, and data modeling
• A short session on how you would raise this team's AI-assisted throughput in your first 90 days