Vice President, Engineering

Sensei Labs is hiring a Vice President, Engineering to lead engineering execution for Conductor, its enterprise strategy execution platform. The role owns technical strategy, architecture, delivery, team development, platform reliability, AI capabilities, and modernization of the product.

Responsibilities:

• Delivery. Planning, sequencing, and shipping against a roadmap you help build with Product. Predictable releases, visible progress, honest tradeoffs
• The team. Coaching and growing six engineers, running performance and career conversations, hiring as we scale, and keeping the bar high without burning people out
• Cloud platform and reliability. Architecture, scalability, cost, and operational excellence for a single-tenant enterprise SaaS platform. Uptime, performance, and security posture are yours. You'll lead our Platform/DevOps team alongside product engineering, setting direction for infrastructure and application architecture, performance and scalability, cloud cost management, and the tooling that the rest of engineering builds on. Uptime, operational excellence, and security posture are yours
• AI in the product. Partnering with Product on how Harmony AI evolves — agentic workflows, retrieval, evaluation, guardrails, and permission-aware AI behavior in an enterprise context
• AI in how we build. Making our SDLC substantially faster and more automated: AI-assisted coding, code review, and test generation; CI/CD; automated quality gates. We want an engineering org where a small team ships like a large one, and you'll be the one who builds that
• Engineering–Product partnership. Working shoulder to shoulder with Product on discovery, scope, and sequencing. You'll be expected to have opinions about the product, not just the plumbing
• Enterprise trust. Security, compliance, and the technical side of customer and prospect conversations when it matters

Requirements:

• You've architected, built, and operated production cloud SaaS at meaningful scale — not just supervised it
• You're fluent across both layers: the application architecture (service boundaries, data modeling, API design, and the patterns that keep a large codebase evolvable) and the infrastructure underneath it
• Hands-on depth in Azure and/or GCP is essential, along with container orchestration on Kubernetes, infrastructure as code, CI/CD pipelines, networking and identity, and the observability and cost discipline that keep a cloud platform healthy as it grows
• You understand multi-tenancy versus single-tenancy tradeoffs, data isolation, performance under enterprise load, and what "SOC-2 compliant" actually costs an engineering team
• You've worked in product-led environments where engineering shapes what gets built
• You can push back on a spec, spot the simpler solution, and reason about customer value — especially in complex B2B software where the user is an enterprise operator, not a consumer
• You've led and grown engineering teams (roughly 5–20 people) as a player-coach
• You've hired well, given hard feedback, and relentlessly tuned the delivery process
• You've shipped AI or LLM-backed features into production — and you've also rebuilt how a team works using AI-assisted development and automated SDLC tooling
• You can tell the difference between AI that creates leverage and AI that creates cleanup work
• You're comfortable being both the strategist and the person who fixes the flaky test
• You'd rather own an outcome than a headcount number
• Enterprise PPM, EPMO, transformation, or professional services domain experience
• Experience with Microsoft 365 / SAP / Jira / Power BI integration ecosystems
• Background in selling or supporting technical evaluations with Fortune 500 or PE buyers
• Experience taking a mature product through an AI-era re-platforming or modernization