Job Overview
Location
Santa Clara
Job Type
Full-time
Category
Software Engineering
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • Lead and grow a small, high-performing team of AI/ML and agent engineers focused on building LeanData’s AI Products platform.
- • Own the technical vision for the AI and agent platform that powers go-to-market automation for fast-growing companies.
- • Drive 0-to-1 development of ambiguous go-to-market problems into production-ready AI features, partnering closely with product, design, and data teams.
- • Set and enforce AI and agent best practices across the entire engineering organization, including evaluation discipline for non-deterministic LLM systems.
- • Design, review, and ship production code alongside engineers, spending approximately half your time hands-on in development.
- • Build and maintain the evaluation infrastructure and abstractions used by other LeanData teams to deploy AI features reliably.
- • Own the quality, reliability, and delivery of all AI outputs, including managing the model and LLM upgrade pipeline with attention to quality, latency, and cost tradeoffs.
- • Define and implement metrics and quality bars for AI systems that are non-deterministic, ensuring consistent performance and user trust.
- • Hire, coach, and mentor engineers to raise the technical bar and scale the team’s capabilities while maintaining a culture of ownership and excellence.
- • Collaborate with engineering leadership to align AI product roadmap with company-wide revenue automation goals.
- • Stay deeply technical: write, review, and debug production Python code; contribute directly to core AI components and infrastructure.
- • Translate business objectives into technical specifications for AI features, ensuring alignment between go-to-market needs and engineering execution.
- • Establish standards for model selection, prompt engineering, and evaluation frameworks that are scalable and reproducible across teams.
- • Monitor and improve the performance of deployed AI systems, identifying bottlenecks and optimizing for efficiency without sacrificing output quality.
- • Serve as the primary technical authority on LLM applications within the company, advising other teams on safe and effective AI integration.
- • Maintain awareness of emerging AI tools, frameworks, and industry benchmarks to ensure LeanData’s platform remains at the cutting edge.
🎯 Requirements
- • 4+ years building and shipping ML or AI/LLM systems in production, including 3+ years managing or leading engineers
- • A track record of building and scaling AI-powered product capabilities 0-to-1, and of growing a small, strong engineering team while staying hands-on
- • Strategic and opinionated: turn ambiguous ideas into production-ready features and defend sharp technical calls to product and engineering leadership
- • Depth in evaluation and quality measurement for non-deterministic AI/LLM systems, including model selection and tradeoffs between quality, latency, and cost
- • Strong, current Python skills; still write and review production code
- • Applied AI experience essential, including building products on large language models and partnering with product, design, and data to shape an AI roadmap
🏖️ Benefits
- • Base salary between $250,000 and $300,000
- • Equity compensation
- • Office-based role with required in-office presence on Mondays and Wednesdays each week
- • Opportunity to lead AI product development at a company powering revenue automation for fast-growing businesses
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About LeanData Inc.
LeanData provides revenue operations software that matches leads to accounts, routes prospects, and orchestrates go-to-market workflows for B2B sales and marketing teams. Its cloud platform deduplicates, enriches, and segments data, then applies rule-based routing to ensure timely, accurate handoffs across territories and channels. Built natively on Salesforce, the solution offers native CRM integration, analytics dashboards, and audit trails to improve conversion rates, pipeline visibility, and revenue attribution for mid-market and enterprise organizations.
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