Senior Data and AI Engineer

Your Future Evolves Here

Evolent partners with health plans and providers to achieve better outcomes for people with most complex and costly health conditions. Working across specialties and primary care, we seek to connect the pieces of fragmented health care system and ensure people get the same level of care and compassion we would want for our loved ones.

Evolent employees enjoy work/life balance, the flexibility to suit their work to their lives, and autonomy they need to get things done. We believe that people do their best work when they’re supported to live their best lives, and when they feel welcome to bring their whole selves to work. That’s one reason why diversity and inclusion are core to our business.

Join Evolent for the mission. Stay for the culture.

What You’ll Be Doing:

Responsibilities

• Lead the design, development, and deployment of complex software solutions, ensuring scalability and maintainability.
• Architect and implement high-performance and data pipelines that support critical business functions.
• Collaborate closely with cross-functional teams, including product managers, UX designers, and other engineers, to translate business needs into technical solutions.
• Conduct thorough code reviews, providing constructive feedback and ensuring adherence to best coding practices.
• Mentor and coach junior engineers, fostering a culture of continuous learning and technical excellence.
• Identify and implement improvements to the software development lifecycle, including automation, testing, and CI/CD pipelines.
• Troubleshoot and resolve production issues, working to ensure high availability and reliability of services.
• Evaluate and integrate new tools, frameworks, and technologies to improve development processes and team productivity.
• Drive the technical vision for projects, contributing to architectural discussions and long-term planning.
• Apply AI-assisted engineering techniques across the full delivery lifecycle, including requirements analysis, pipeline and code development, testing, debugging, documentation, and operational monitoring.
• Iterate with AI on solution design and architecture, evaluating alternatives, revising existing architecture, and producing design artifacts for review.
• Set the standard for validating AI-generated outputs for correctness, security, maintainability, compliance, and business appropriateness, including when reviewing the AI-assisted work of other engineers.
• Design and support data platforms and governed datasets that enable machine learning, analytics, and generative AI workloads.
• Contribute reusable prompts, skills, agents, engineering playbooks, and AI-assisted development patterns that benefit the broader engineering organization.
• Ensure AI usage complies with enterprise policies for intellectual property protection, security, privacy, PHI handling, and Responsible AI standards.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
• 5+ years of professional software development experience, with a proven track record of delivering complex, scalable applications.
• Proficiency in one or more programming languages, such as C# or Python, and relevant frameworks.
• Knowledge of cloud platforms (e.g., Azure, AWS, GCP), and experience with data engineering technologies (e.g., Spark, Databricks, Microsoft Fabric)
• Knowledge and experience with modern data engineering patterns (e.g., Data Vault, dimensional modeling, data products, lakehouse architecture, feature flags, event-driven systems, DAGs).
• Expertise in database design and optimization for both SQL and NoSQL databases.
• Excellent problem-solving skills, with the ability to diagnose and resolve complex technical issues quickly.
• Strong communication skills, with the ability to lead technical discussions, present to stakeholders, and write detailed documentation.
• Demonstrated experience using AI-assisted development platforms such as GitHub Copilot, Cursor, Claude Code, or similar tools to deliver production work.
• Strong prompt engineering skills, with experience in AI-assisted testing and AI-enabled delivery practices.
• Experience with machine learning data pipelines, vector search technologies, document processing pipelines, or AI data preparation techniques.
• Working knowledge of data governance, lineage, quality, and observability practices supporting AI-enabled solutions….