Senior Software Engineer (AI)

Cotiviti•Remote,

5d•$111,000 - $150,000•Remote

About The Position

Senior Software Engineer (AI) is a hands-on role responsible for building intelligent backend services and workflow-integrated solutions within an AI-native development environment. This role combines strong Java-based engineering expertise with enterprise workflow orchestration to enable automation, intelligent routing, and AI-assisted decisioning. The engineer will support the Payment BU Workflow Intelligence & Orchestration Initiative, collaborating with Technical Architects and engineering teams to deliver scalable, secure, and reusable services across workflow platforms. The role leverages AI-assisted engineering tools (Claude, Copilot) to accelerate development while ensuring validation, quality, and adherence to enterprise standards.

Requirements

Bachelor’s degree in Computer Science, Engineering, or equivalent
5+ years of backend / enterprise software development experience
Strong expertise in Java, Spring Boot, microservices
Strong expertise in REST APIs and integration patterns
Strong expertise in Workflow orchestration platforms (Temporal, Camunda, Flowable, JBPM, Drools)
Experience integrating AI-driven capabilities into enterprise applications
Experience with PostgreSQL / Oracle (data modeling, performance tuning)
Experience with Event-driven and distributed systems
Experience with CI/CD, DevOps, container platforms (OpenShift, Kubernetes, AWS)
Familiarity with AI-assisted development tools (Copilot, Claude)
Agile experience (SAFe preferred) and strong communication skills
Critical Thinking: Ability to think critically and evaluate information objectively, considering different perspectives and potential implications before drawing conclusions or making recommendations.
Attention to Detail: must have a keen eye for detail to ensure accuracy in data analysis, interpretation, and reporting.
Quantitative Aptitude: Strong numerical skills are essential for conducting quantitative analysis, working with statistical methods and models, and manipulating data using mathematical operations.
Data Interpretation: skilled in interpreting data visualizations, charts, graphs, and other forms of data presentation to extract meaningful insights and communicate findings effectively.
Communication Skills: Effective communication skills are crucial for conveying complex technical concepts and insights to non-technical stakeholders clearly and understandably through written reports, presentations, and verbal discussions.
Curiosity and Learning Agility: A strong desire to learn and explore new methodologies, techniques, and tools in the field of data analysis and insights generation is essential for staying current with industry trends and best practices.
Resilience: The ability to handle pressure, adapt to changing priorities, and overcome setbacks is important in a fast-paced and sometimes ambiguous analytical environment.
Ethical and Integrity: Upholding ethical standards and maintaining integrity in handling sensitive data and information is paramount for building trust and credibility in the insights provided
Remaining in a stationary position, often standing or sitting for prolonged periods.
Repeating motions that may include the wrists, hands and/or fingers.
Must be able to provide a dedicated, secure work area.
be able to provide high-speed internet access / connectivity and office setup and maintenance.

Nice To Haves

Experience building workflow-driven and decision automation solutions
Exposure to AI-native development practices and prompt-assisted workflows
Experience with enterprise workflow platforms (Appian or similar)
Experience contributing to shared platforms or integration frameworks
Knowledge of governance practices for AI-assisted development
Background in Healthcare IT or regulated environments

Responsibilities

Design and develop backend services and APIs using Java (Spring Boot, microservices)
Integrate services with workflow engines (Temporal.io, Camunda, Flowable, JBPM, Drools) and platforms such as Appian
Build and expose AI-enabled service capabilities for workflow automation and decision support
Use AI-assisted tools (Claude, Copilot) for code generation, testing, documentation, and development acceleration
Implement AI-native workflow patterns, including intelligent routing, context-aware processing, and embedded decision support
Develop microservices and event-driven architectures supporting distributed workflow execution
Collaborate with data teams for data access, validation, and transformation
Support service orchestration and runtime workflow execution
Contribute to CI/CD, DevSecOps, and cloud-native deployments on OpenShift / Kubernetes and AWS
Participate in code reviews, design discussions, and cross-team collaboration