Sr Software AI Engineer

Responsibilities:


AI-Native Engineering

Build and enhance production-grade Java/Spring Boot backend services, APIs, and microservices using AI-assisted workflows (Claude, Copilot) for coding, testing, debugging, and documentation.

Review, validate, and refine AI-generated code for correctness, performance, security, and maintainability.

Integrate services with workflow orchestration platforms (e.g., Temporal.io, Camunda) to support automation, intelligent routing, and decision support.

Orchestrate AI tool usage across development activities and help refine AI-native engineering standards set by the Tech Lead.



Collaboration & Delivery

Collaborate with the AI-Native Tech Lead, data teams, and adjacent teams to deliver features end-to-end, balancing speed, quality, and long-term maintainability.

Participate in design discussions and code reviews; communicate technical issues and tradeoffs clearly to engineering and product stakeholders.



Quality & Continuous Improvement

Ensure adherence to client technology standards, secure coding practices, and SDLC requirements; resolve production issues and improve system performance and reliability.

Contribute to CI/CD, DevSecOps, and cloud-native deployments (OpenShift/Kubernetes, AWS).

Continuously build AI-assisted development knowledge and help improve team engineering practices. Complete all responsibilities on the annual Performance Plan and any special projects/duties as assigned.


Required Qualifications:


Required

BS or MS in Computer Science, Information Technology, Engineering, or equivalent experience.

5+ years of professional backend/enterprise software engineering experience.

Strong proficiency in Java, Spring Boot, and microservices architecture, with solid REST API and integration-pattern experience.

Demonstrated experience building and shipping production applications, using AI-assisted tools (Claude, Copilot, or similar) as part of daily workflow.

Strong debugging, problem-solving, and code-review skills, with a detail-oriented, ownership-driven approach to quality.

Experience with relational databases/SQL (PostgreSQL/Oracle), data modeling, and performance tuning.

Experience with event-driven/distributed systems and CI/CD, DevOps, and container/cloud platforms (OpenShift, Kubernetes, AWS).

Exposure to workflow orchestration platforms (Temporal, Camunda, Flowable, JBPM, or Drools).

Strong communication and collaboration skills; ability to learn quickly in a fast-evolving technical environment; Agile experience (SAFe preferred).



Preferred Qualifications

Experience building workflow-driven or decision-automation solutions, or with enterprise workflow platforms (Temporal.io or similar).

Exposure to AI-native development practices, prompt-assisted workflows, and governance practices for AI-assisted development.

Experience contributing to shared platforms/integration frameworks, or building internal developer tools and automation.

Experience with cloud platforms (AWS, Azure, OCI) and containerization (Docker, Kubernetes).

Background in Healthcare IT or regulated environments.