Sr Software AI Engineer

Role: Sr. Software AI Engineer
Location: Blue Bell, PA (Remote)

Let’s create our future together at The AES Group!

About The AES Group
The AES Group is a premier technology and engineering consulting company that has been bringing businesses and talent together for over 20 years to deliver innovative solutions that have the greatest positive impact on society. AES has helped over 40 business enterprises, including Fortune 500 companies, engage their customers, empower their employees, and transform their business operations with the power of cloud, data, AI, engineering, and other emerging technologies.

About the role:
The Senior Software Engineer I (AI) is a senior individual contributor on a small, focused AI-Native team, building production software using AI-native development workflows under the guidance of the AI-Native Tech Lead. AI Engineers use AI tools (Claude, Copilot) as a first-class part of their daily workflow to accelerate development, testing, and feedback loops -- applied on top of a strong backend/enterprise foundation in Java, Spring Boot, microservices, and workflow orchestration platforms. This role is not focused on training AI models or building ML pipelines; it is about building software efficiently, safely, and at high quality using AI-assisted engineering practices.

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 Cotiviti 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:
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.