Director, GTM AI Engineering
New
S
SamsaraAI engineering
This is a remote position open to candidates residing in the US.Full-TimeDirector
Salary$182,000 — $325,000 USD
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Job Details
- Experience
- 10+ years across software engineering, machine learning, data science, or data platforms, including meaningful leadership experience.
- Required Skills
- AWSPythonSalesforceTypeScriptDatabricks
Requirements
- 10+ years across software engineering, machine learning, data science, or data platforms, including meaningful leadership experience.
- Regularly write code.
- Bachelor’s degree or equivalent relevant work experience.
- Hands-on experience building and shipping LLM applications and agentic workflows to production, including tool use, retrieval, context engineering, and production reliability.
- Production full-stack and cloud engineering experience, for example Python or TypeScript, AWS, and Databricks, including ownership of systems other teams depend on.
- Experience designing and running evaluation frameworks for LLM or agent systems and using them to drive quality decisions.
- Daily, fluent use of AI agents and coding assistants in your own work.
- Track record of shipping internal or customer-facing AI/ML products with measurable business impact.
- Experience with predictive modeling, experimentation, analytics, and data engineering foundations.
- Strong product judgment and ability to turn ambiguous business problems into simple, valuable solutions.
- Excellent communication with executives and frontline users, including presenting and demonstrating products.
- People-first leadership experience hiring, developing, and retaining technical talent.
Responsibilities
- Prototype, ship, and iterate on AI agents, copilots, and workflow automations for GTM teams.
- Own the architecture of the shared GTM AI platform, including orchestration, LLM and tool gateways, identity and access, and MCP and SDK contracts.
- Design and run evaluation frameworks for agent and LLM behavior, using golden datasets, LLM-as-judge, human review loops, and regression suites.
- Use agents, coding assistants, and agent harnesses in daily work and build shared tooling and patterns for the team.
- Track new models, agent frameworks, MCP and tool ecosystems, and context engineering; make practical recommendations and build-versus-buy decisions.
- Advocate for AI across Sales, Customer Success, and Support through demos, field feedback, and adoption support.
- Own GTM AI technical and product strategy, including data foundations, instrumentation, governance, observability, model routing, and per-user spend controls.
- Own forecasting, propensity, and CRM data-quality work, keeping it calibrated and validated.
- Partner with GTM, Product, and Engineering leaders to identify opportunities, define success metrics, and build durable products.
- Establish responsible-AI practices for safety, privacy, reliability, least-privilege permissions, and human approval of changes to systems of record.
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