Senior Director Principal Software Engineer – Forward Deployed

Role Summary

Senior Engineering Leader to drive high-impact, AI-enabled software systems across the Commercial Analytics domain. This role combines hands-on technical leadership, architectural ownership, and executive partnership to deliver reliable, scalable solutions with speed and rigor. It is a forward-deployed, startup-CTO–style role embedded within the Commercial business unit, partnering with business leaders to solve real problems and rapidly prototype scalable solutions. The ideal candidate blends executive communication, deep technical judgment in commercial analytics, and modern AI-augmented engineering practices; hybrid work location.

Responsibilities

• Lead delivery of the most critical Data, Analytics, and AI initiatives across Commercial Analytics.
• Own technical strategy and architecture, ensuring solutions are scalable, reliable, and business-aligned.
• Establish engineering standards for design, development, testing, and AI-assisted delivery.
• Drive rapid prototyping and MVP development from concept to production.
• Lead adoption of AI-augmented development tools and workflows.
• Define governance, evaluation, and human-in-the-loop verification standards for AI-assisted work.
• Evaluate and integrate emerging AI/ML technologies into engineering practices.
• Lead and mentor a matrixed team of engineering leaders and senior engineers.
• Shape talent strategy, including hiring, succession planning, and senior-level development.
• Build a culture of engineering excellence, collaboration, and continuous learning.
• Act as a trusted technical advisor to VP/SVP Commercial leaders.
• Translate technical trade-offs into business impact and investment decisions.
• Influence commercial analytics strategy and long-term technology roadmaps.
• Define reliability standards (SLOs/SLIs) and champion operational excellence.
• Ensure strong observability, monitoring, and production readiness.
• Lead post-incident learning and continuous reliability improvements.
• Establish clear documentation and spec-driven development standards.
• Build scalable knowledge-management practices across teams.
• Improve delivery flow through lean methods, process simplification, and systematic bottleneck removal.

Qualifications

• Required: Bachelor’s degree in Computer Science, Engineering, Data Science, Business Analytics, or related field; 12–15+ years of experience.
• Required: Proven experience delivering analytics and technology solutions in partnership with Commercial leaders, ideally in life sciences.
• Required: Deep knowledge of Life Sciences Commercial Analytics use cases (e.g., forecasting, market research, omnichannel, customer analytics, marketing mix modeling, Next Best Action).
• Required: Experience leading end-to-end MVPs with engineering, data science, and vendor teams.
• Required: Background scaling data, analytics, and ML platforms in large organizations.
• Required: Strong executive presence and ability to operate as a strategic advisor.
• Preferred: Master’s degree in Computer Engineering, Data Science, or Business.
• Preferred: Hands-on experience with platforms such as Databricks, Snowflake, AWS, or Azure.
• Preferred: Experience influencing cross-functional teams without direct authority.
• Preferred: Prior experience at a top-tier technology or management consulting firm.

Education

• Master’s degree in Computer Engineering, Data Science, or Business. (Preferred)