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Principal Engineering Leader, Healthcare Data & AI

Job in New York, New York County, New York, 10261, USA
Listing for: Fractal
Full Time position
Listed on 2026-10-17
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), IT Project Manager
Salary/Wage Range or Industry Benchmark: 200000 - 265000 USD Yearly USD 200000.00 265000.00 YEAR
Job Description & How to Apply Below
Location: New York

Fractal is a strategic AI partner to Fortune 500 companies, with a bold vision: to power every human decision in the enterprise. We believe the future belongs to organizations that combine human imagination with intelligent systems and Fractalites are the ones building that future.

As we scale our Healthcare and Life Sciences (HLS) practice in the United States, we are looking for a Principal Engineering Leader to serve as the senior technical leader for the practice. You will be the technical face of Fractal HLS in front of client CIOs and CTOs, leading pre-sales, shaping solutions, and helping us win and grow large Data & AI programs.

This is not a delivery or single-project role. It is a client-facing, practice-wide leadership position for someone who can command respect from senior technology executives, lead technical pursuits end to end, and build a team of senior architects and engineering leaders underneath them.

Location:

New York City, NY

The Opportunity

As Principal Engineering Leader for Healthcare Data & AI, you will own the technical side of the HLS portfolio, from pre-sales and solution design through oversight of high-stakes implementations. You will front every major technical conversation with clients and make sure ambitious business goals turn into secure, scalable, production-grade AI platforms.

You will:
  • Lead pre-sales and RFPs: own technical pursuits across the HLS portfolio, including solution design, architecture, effort and cost positioning, and orals, to help Fractal win new programs and expand existing accounts.
  • Be the technical voice with client executives: hold credible, peer-level conversations with CIOs, CTOs, and CDOs on AI platform strategy, architecture, cloud spend optimization, and modernization roadmaps.
  • Shape enterprise AI and data platforms: guide the architecture of AI platforms built on Databricks, Azure, and AWS, including context layers, AI gateways, and agentic AI solutions grounded in enterprise data.
  • Front-end high-stakes engagements: stay close to critical programs as the senior technical lead with the client, while your team owns day-to-day delivery.
  • Build and lead the team: manage a group of senior architects and engineering leaders (starting with 3 to 4 direct reports, growing over time), with broader indirect teams across the US.
  • Grow the portfolio: help drive technology product sales and implementations across a portfolio of roughly $20M.
  • Industrialize AI and GenAI: help clients move from experimentation to enterprise-scale impact through strong governance, security, and MLOps/LLMOps/Agent Ops practices.
What Makes This Role Compelling
  • Practice-wide influence: you will be the most senior technical leader in the HLS practice, shaping how we sell and build for some of the largest healthcare and life sciences organizations.
  • Direct line to the business: you will report into HLS practice leadership and play a central role in growing revenue.
  • AI-first mandate: you will drive adoption of AI platforms, GenAI, and agentic AI across client programs.
  • A values-driven company: Fractal is consistently recognized as a Great Place to Work, with a culture built around curiosity, diversity, and long-term thinking.
Qualifications & Experience
  • AI platform experience (non-negotiable): hands-on experience shaping and delivering AI platforms, including context layers, AI gateways, agentic AI, and Databricks-based AI capabilities.
  • Pre-sales and executive presence: proven track record leading technical pre-sales, RFP responses, and solutioning, and driving technical discussions directly with CIO/CTO-level leaders.
  • Databricks, Azure, and AWS: strong working knowledge of Databricks plus at least one of Azure or AWS (ideally both). Breadth across the stack matters more than deep…
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