Senior Software Engineer (AI)

Cotiviti is a company focused on building intelligent backend services and workflow-integrated solutions within an AI-native development environment. The Senior Software Engineer (AI) will design and develop backend services using Java, collaborate with technical teams, and leverage AI-assisted tools to enhance development processes.

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, development acceleration
• Implement AI-native workflow patterns, including: intelligent routing, context-aware processing, 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: OpenShift / Kubernetes, AWS
• Participate in code reviews, design discussions, and cross-team collaboration

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
• REST APIs and integration patterns
• Workflow orchestration platforms (Temporal, Camunda, Flowable, JBPM, Drools)
• Experience integrating AI-driven capabilities into enterprise applications
• Experience with: PostgreSQL / Oracle (data modeling, performance tuning)
• Event-driven and distributed systems
• 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
• 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