Staff Software Engineer at CaptivateIQ leading AI strategy and architecture for enterprise sales performance solutions. Collaborating with teams on foundational AI systems and technical direction.
About the role
- Senior Director of AI Engineering and Delivery overseeing enterprise AI and Generative AI platforms. Leading technical teams in a highly regulated environment within the medical technology sector.
Responsibilities
- The Head of AI Engineering and Delivery will lead the design, build, and evolution of enterprise AI and Generative AI teams and platforms for a global organization operating in life science, medical technology-driven markets.
- This leader will bring deep technical credibility across software engineering, data engineering, AI / machine learning, and cloud-native architecture, combined with a proven ability to build and lead technical teams operating within a highly regulated environment.
- The role is responsible for creating reusable, secure, and scalable AI capabilities that empower product teams, business units, and operations to rapidly develop and deploy AI-driven solutions.
- The role will serve as a senior engineering and architecture authority for AI platforms, ensuring consistency, governance, and speed while enabling innovation across the enterprise.
Requirements
- 15+ years of experience in software engineering and large-scale platform development.
- Demonstrated success building and scaling enterprise platforms in financial services, fintech, or global technology firms.
- Strong expertise in: Distributed systems and modern software architecture, Cloud platforms (AWS, Azure, GCP) in regulated environments, API, microservices, and event-driven architectures, Platform reliability, observability, and cost management.
- Proven track record delivering production AI and ML systems in real-world, regulated contexts.
- Hands-on experience with: Machine learning lifecycle management (MLOps); Model monitoring, retraining, and performance management; Generative AI and foundation models (LLMs); RAG, prompt orchestration, evaluation, and guardrails;
- Experience operationalizing AI with risk controls, explainability, and governance.
- Experience leading large, globally distributed engineering teams.
- Strong stakeholder management skills across Technology, Risk, Compliance, and Business leadership.
- Demonstrated ability to shift organizations toward platform-led, reuse-driven delivery models.
- Track record of aligning AI platform investments to revenue growth, cost efficiency, risk reduction, or customer outcomes.
- Bachelor’s degree in computer science, engineering, or a related technical discipline required. Advanced degree (Master’s or PhD) in Computer Science, AI, Machine Learning, or Data Science preferred.
Benefits
- Not Applicable
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