Chief Technology Officer

Blooming Health

119d•Hybrid

About The Position

Blooming Health is on a mission to transform social care! Our AI-powered platform identifies social needs and barriers by continuously collecting real-time data from member interactions and screenings. It then drives action through automated, empathetic outreach in 55+ languages/dialects to engage individuals across voice, SMS, and email, and coordinating referrals to the right services at the right time. The result is improved access to care, higher program participation, and better outcomes across diverse populations. Our platform supports 1,000+ community organizations across the US, helping millions of members access the support they need to stay healthy. We don’t just offer software—we deliver impact. As we scale, we’re looking for a strategic and execution-driven Chief Technology Officer (CTO) to own our technical and AI strategy. We do have a strong preference for NY-based candidates, but it is not a requirement.

Requirements

12+ years of progressive engineering experience with 5+ years as a CTO, VP of Engineering, or equivalent senior technical executive at a high-growth B2B SaaS company.
Track record of leading technical organizations through critical inflection points.
Demonstrated success integrating and scaling AI/ML products (LLMs, agents, predictive models) within production environments.
Deep familiarity with modern AI architectures and the build-vs-buy decision framework.
Proven ability to recruit, retain, and develop elite technical talent.
Track record of building lean, high-performing teams that out-execute much larger organizations.
Deep technical credibility across modern cloud architectures (GCP/AWS), APIs, microservices, and data pipelines.
Capable of guiding strategic build-vs-buy and platform decisions and partnering effectively with senior architects.
Experience managing engineering and AI/research budgets with measurable ROI.
History of reducing coordination overhead while maximizing output per dollar.
Expertise establishing IT, security, and compliance frameworks — including data privacy, IAM protocols, and technical risk mitigation.
HIPAA, SOC2, or HITRUST experience required.
Experience implementing documented feedback loops, succession planning (“Shadow Pipelines”), and zero-downtime delivery practices that scale predictably under pressure.
Strong cross-functional partnership skills with Marketing, Operations, BD, and the executive team.
Excellent communication and influencing skills with both technical and business stakeholders.

Nice To Haves

Direct experience in health tech, particularly with EHR integrations (Epic/Cerner, FHIR), HIPAA, and the payer/provider ecosystem.
Experience leading geographically distributed engineering and AI teams, including India-based teams, with sensitivity to communication, cultural nuance, and operational cadence for global teams.
Familiarity with the MLOps lifecycle, model governance, and managing teams building data-intensive applications.
GCP, MongoDB, PostgreSQL, Node.js, and modern AI/ML frameworks.

Responsibilities

Serve as the primary architect for the technical and AI roadmap, pivoting the organization from tactical management to high-velocity, intelligence-driven delivery.
Lead and mentor a consolidated team of elite, vetted experts, prioritizing high talent density over volume to ensure 100% certainty in AI and backend execution.
Oversee the integration and scaling of core AI/ML initiatives, ensuring robust architectures that maintain a competitive edge in the health-tech ecosystem.
Manage and optimize the engineering and AI research budget, demonstrating clear ROI by reducing coordination overhead and maximizing output per dollar.
Establish and enforce rigorous IT and compliance standards, with specific focus on data privacy for AI models, IAM protocols, and technical risk mitigation.
Partner directly with executive leadership across Marketing, Operations, and Business Development to align AI capabilities with aggressive organizational growth targets.
Implement documented feedback loops and “Shadow Pipelines” to identify high-potential AI/ML talent and mitigate key-person dependency risks.
Act as the stabilizing force during technical transitions, ensuring seamless knowledge transfer of complex AI systems and zero-downtime execution during lead-level rotation.
Architecting systems and strategy for a globally distributed engineering footprint, ensuring high performance across diverse regions.
Leading the organization’s pivot toward an AI-first product ecosystem, integrating LLMs and proprietary ML models into core offerings.
Balancing aggressive technical innovation with the security and compliance requirements of a scaling global enterprise.