Data Engineering Manager leading data infrastructure for global fleet analytics at Lime. Overseeing data warehousing, governance, and supporting data operations and ML initiatives.
About the role
- Engineering Manager leading AI-first software development for a new EMR platform at Intrahealth. Overseeing engineering teams and shaping development practices for healthcare software.
Responsibilities
- Own outcomes for the team: delivery, quality, operability, and predictability.
- Manage commitments, scope, and trade-offs with stakeholders.
- Lead AI-first engineering execution across pods: Define and evolve how work is structured across multiple pods, including ownership boundaries, dependencies, and delivery coordination.
- Establish and scale AI-first development practices across pods, including how engineers use AI tools, agentic workflows, code generation, verification loops, and review discipline.
- Create clear ways of working that support autonomy within pods while maintaining alignment across the broader platform.
- Greenfield AI-first delivery leadership: Help shape and build the engineering organization, systems, and practices required to deliver a new EMR platform from the ground up.
- Drive clarity in ambiguous problem spaces, turning product and technical goals into actionable, testable increments using AI-first development approaches.
- Ensure the team builds systems that maximize engineering leverage through AI, automation, and strong delivery workflows.
- Technical leadership: Guide system architecture and engineering practices across the new platform, including frontend, backend, APIs, and shared services.
- Ensure the new system is scalable, secure, accessible, and maintainable.
- Partner with senior engineers and architects to make sound technical decisions and manage cross-pod technical risk.
- Provide technical leadership on where and how AI-assisted and agentic development should be applied, and where guardrails are required.
- Quality and risk management: Implement CI/CD quality gates (unit/integration/e2e), regression protection, static analysis, dependency controls, and release checks.
- Define and enforce security/privacy-minded practices appropriate for healthcare data.
- Establish guardrails and validation practices so AI-assisted development remains correct, maintainable, and auditable.
- People leadership: Coach engineers and technical leads in AI-first development practices and create a healthy, accountable engineering culture grounded in strong engineering habits (testing, design, PR discipline, operational ownership).
- Support career growth, performance management, and team development across a growing organization.
- Build a learning culture that helps the team keep pace with rapidly evolving AI tooling without destabilizing delivery.
- Cross-functional execution: Partner with Product to shape work into well-specified, testable increments.
- Communicate clearly to technical and non-technical stakeholders, escalating risks early with concrete mitigation.
Requirements
- 7+ years of industry experience building production software
- Demonstrated experience managing engineers across multiple teams, pods, or workstreams in a product engineering environment
- Demonstrated hands-on fluency with AI-assisted development tools and agentic workflows; AI fluency is a must-have and the most important skill for this role
- Proven ability to operationalize AI-first development into reliable delivery systems, practices, and guardrails rather than ad-hoc usage
- Proven ability to lead greenfield or early-stage product development through ambiguity and change
- Strong technical judgment and fluency in modern software engineering practices, including architecture, APIs, data modeling, CI/CD, performance, reliability, and testing
- Strong React and .NET engineering background, with the ability to guide technical direction credibly across the stack
- Strong problem-solving and analytical skills, and the ability to debug complex system and organizational delivery issues, including failures in AI-assisted workflows
- Excellent communication skills and stakeholder management; ability to set expectations and deliver predictably.
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