Key Responsibilities

Toolset standardization: Consolidate tools to as few systems of record as possible, with a single source of truth for SDLC
SDLC end-to-end: Own Linear, partner to set real deadlines, hold the line on them, and give leadership an accurate six-month forward view of capacity across Applied AI, Engineering and Research
Design automated development workflows that can keep pace with AI-accelerated engineering, ensuring that compliance, security, and privacy reviews are inherently baked into the system
The FDE-to-Engineering handoff: Formalize the path that pulls FDE-built extensions into the core platform; determine when extensions get productized, when they get deprecated, and when functionality folds into the core model
Cross-team coordination: Run the operating rhythm that connects Applied AI, Engineering, and Research; kill the downtime on blocked dependencies across SF, Europe, and Israel
API & Technical Specification Alignment: Act as the facilitator for cross-team technical definitions; prevent delivery bottlenecks by ensuring early agreement on API signatures, terminologies, and system design before Engineering is asked to build
Delivery accountability: When a capability is built but stuck before launch, get it across the line
Operational reviews: Establish and run a weekly or biweekly review with engineering leadership that surfaces what's on track, what's blocked, and what needs an executive decision
Collaboration: Work across departments (Marketing, Sales, etc.) for collaboration, communication and coordination

Requirements

7+ years in technical program management, engineering management, or a hybrid role at a high-growth software or AI company
Direct experience with the machine learning or LLM development lifecycle
Track record of standing up SDLC and tooling at a company in the 50 to 300 person range
Comfort with ambiguity and authority; coordinating senior engineers and researchers without managing them
Experience coordinating engineering across multiple time zones, ideally including the US/Europe/Israel triangle
Strong written communication

Nice to Have

Background in enterprise B2B SaaS, especially companies with both a platform motion and a Forward Deployed Engineering or solutions motion (Palantir, Databricks, Snowflake, Scale, Sierra, and similar)
Experience working alongside an FDE or applied team where customer-built work needs to be productized
Familiarity with model deployment, inference infrastructure, or MLOps at production scale