Practice Area
Healthcare IT
Region
Anywhere
Location
On-Site
Company Location
Austin TX
Position Id
48044

Head of Engineering

Job Description
Client Summary:
  • Specialized AI tools designed specifically for healthcare workflows
  • Helps healthcare teams interpret and organize unstructured information like notes, claims, and documents
  • Reduces manual work and improves decision-making efficiency across clinical and administrative tasks
  • Supports organizations such as health insurers, providers, and medical research groups
  • Demonstrated impact on care management speed, error reduction, and compliance reporting
  • Tailored to understand complex medical language and systems
  • Enables faster, more accurate reviews and operational performance without generic AI limitations
Position Responsibilities:
  • Technical Leadership & Strategy
    • Define and evolve our platform and product roadmap aligned with business priorities and customer expectations
    • Guide architectural decisions across ML pipelines, APIs, and enterprise integrations
    • Work closely with leaders to collaborate and execute on the product vision
    • Be a partner to Product and sales/go-to-market leaders to align platform investments with business outcomes.
    • Own infrastructure scalability (Kubernetes on various clouds), data security, and compliance (HIPAA, HITRUST, SOC2) working with CISO
  • Team Building & Execution
    • Own and evolve a high-leverage engineering org structure that scales across geographies and product lines.
    • Oversee best-in-class processes across CI/CD, code quality, information security, and observability to realize AgentOps lifecycle
    • Establish a release cadence by shipping product releases on a regular basis
    • Identify and grow technical leaders, create pathways for autonomy, and eliminate process friction.
    • Partner with customer solutions and forward deployment teams to accelerate delivery of product capabilities without sacrificing quality and stability
    • Build for resiliency and scale in mind — not just speed. You reduce toil through automation and uplift long-term system health.
  • Collaboration & Representation
    • Act as the face of Engineering with strategic customers, demonstrating deep platform knowledge and inspiring confidence
    • Understand customer infrastructure needs into scalable product capabilities that can be easily configured for customer deployments
    • Ensure our platform can support high-volume clinical workflows, interoperability, and analytics by creating and testing capabilities
    • Align GTM, Product, and Customer Ops to ensure delivery excellence and rapid iteration on feedback
Experience & Skills:
Required Experience and Qualifications:
  • 10+ years of engineering experience, including 5+ in leadership roles building enterprise Data and AI systems
  • Built and led teams working with healthcare payers and/or large provider systems in a fast-paced setting like startups
  • Deep understanding of enterprise healthcare infrastructure, ML and data pipelines, and APIs (e.g. HL7, FHIR, EHR integrations), Application integration such as QNXT, Pega, Salesforce
  • Strong track record of shipping secure, compliant, production-grade software in health tech
  • Technical Knowledge & Deep Expertise
    • Prior experience in AI/ML infrastructure or knowledge automation using Agentic AI and Generative AI technologies and frameworks
    • Working knowledge of Generative AI patterns such as RAG, GraphRAG as well as prompt engineering best practices
    • Familiar with tools Kubernetes, Keda, Kafka, Agentic AI frameworks like LangGraph, Langchain, LlamaIndex, database technologies including fitment of product needs, and modern DevSecOps stacks
    • Help with navigating enterprise security, info sec. audits and vulnerabilities by automating common DevSecOps processes within the toolchain
    • Deep expertise is setting up scalable workload configurations in Kubernetes using common best practices such as pod and node autoscaling
  • Efficiency & Streamlined Processes
    • Review and optimize costs on infrastructure spend by creating dashboards with visibility into real-time spend metrics across SaaS and internal environments.
    • Optimize spend by evaluating instance types, GPU instances, execution patterns such as batch jobs for long running processes
    • Ensure faster installation of our platforms using IaC best practices such as Helm, Terraform automation resulting to a one-click deployment option or developing Agents
    • Streamline environments from creation to de-commissioning them across internal and customer environments
    • Establish quality gates from developer workstations to build systems using known tools such as Pylint, Pytest, SonarCube, Snyk