Senior AI Systems Engineer: Data Pipelines & ML

How you will help

Accelerate customer and partner needs into clear, reliable, and scalable data and AI solutions, while strengthening Health Verity’s engineering framework through real-world application and feedback.

As an AI Staff Engineer at Health Verity, you will embed with customers and cross-functional teams to rapidly translate complex business problems into well-designed data flows, AI-enabled capabilities, and production-ready systems. You will help turn fragmented or bespoke customer requirements into smooth, repeatable data processes that align with our platform strategy.

Through hands-on delivery, you will also advance Health Verity’s engineering and AI frameworks; validating patterns, surfacing gaps, and shaping standards that make it easier for teams to build, deploy, and operate intelligent data products at scale.

What you will do

• Lead technical discovery engagements with customers or internal partners to deeply understand business workflows, constraints, data realities, and success criteria.
• Rapidly prototype and iterate on pragmatic solutions; often using AI/ML, data pipelines, and backend services to validate value early and reduce delivery risk.
• Design and deliver production ready systems, including APIs, data pipelines, ML workflows, and cloud-native services, aligned with Health Verity’s architecture and security standards.
• Own deployments and scaling efforts, troubleshooting complex issues across data, infrastructure, and application layers in real customer environments.
• Translate field learnings into leverage, feeding actionable insights back into product strategy, platform roadmap decisions, and reusable engineering patterns.

How success will be defined

• Successfully deliver multiple high-impact customer or partner engagements, translating ambiguous business needs into production-ready technical solutions.
• Drive adoption and demonstrated the value of Health Verity platform capabilities within real customer environments.
• Build strong, trusted relationships with customers and internal stakeholders, reflected in consistently positive feedback on technical delivery and collaboration.
• Influence product and platform direction by bringing concrete, field-driven insights into roadmap, architecture, and prioritization discussions.
• Leave behind durable, maintainable solutions and reusable patterns that scale beyond individual engagements.

Required skills and experience

• 8+ years of software engineering experience, delivering production systems in Python, and/or JavaScript/Type Script.
• Experience building data-intensive, distributed systems, including APIs, data pipelines, and cloud-native services (AWS or similar).
• Demonstrated experience owning and product ionizing AI/ML solutions—taking them beyond experimentation into reliable, monitored workflows and systems
• Strong ability to operate in ambiguous, customer-driven problem spaces and make sound technical decisions.
• Clear communicator with the ability to work effectively across engineering, product, and customer teams.

Desired skills and experience

• Experience working in regulated or compliance-driven environments (e.g., healthcare, life sciences, financial services).
• Background in customer-facing or domain-embedded engineering roles (e.g., forward-deployed, solutions, or consulting).
• Familiarity with modern data platforms and analytical workloads (e.g., Databricks, Spark, Snowflake).
• Experience influencing product or platform direction through real-world delivery or field-driven insights.

Base salary for the role is commensurate with experience and can range between $170, + annual bonus opportunity.

Our main office is located in Center City, Philadelphia, where we operate on a hybrid model with in-office work required three days a week for local employees. We believe collaboration is most effective when teams come together, which is why we prioritize hiring in the Philadelphia area.

For certain roles, we also hire from hub locations —regions where we have an established presence with multiple team members working remotely. While these employees primarily work from home, we bring them together in person at lease once a year for…