Skills this job asks for
A/B testingProduct managementLLMsCustomer successStakeholder managementLeadershipMachine learningStatistics
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Where you can work from
United States only
Based on the listing's location: Remote - US.
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Visa sponsorship, if you would relocate
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal: ask the recruiter.
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No government sponsor record hereThis employer does not appear with approvals in the government data SponsorApply holds.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Before you apply
Sponsorship unknown
No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
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About the role
This is Engineering at Lattice
Lattice's Engineering team is dedicated to building cutting-edge solutions that empower people and organizations to thrive. As AI becomes fundamental to every product experience, ensuring those systems are trustworthy, measurable, and continuously improving is one of the company's most important engineering challenges.
The AI Intelligence Quality (IQ) team owns that challenge. We build the AI Platform that enables every AI team at Lattice to measure quality, detect regressions, run experiments, and continuously improve AI performance with confidence. The platform you lead won't power a single product—it will shape the quality of every AI experience we deliver, becoming a foundational capability for how AI is built at Lattice.
What You Will Do
• Lead, coach, and grow a high-performing team of AI and software engineers, developing them into strong technical leaders while fostering a culture of ownership, technical excellence, experimentation, and continuous learning.
• Own the execution and delivery of the AI Platform roadmap, balancing near-term product impact with long-term platform investments.
• Partner closely with Product, Applied AI, Data Science, and engineering leaders to define how AI quality is measured, evaluated, and continuously improved across Lattice.
• Lead the development of AI evaluation infrastructure, quality metrics, experimentation capabilities, observability, and developer tooling that enable every AI product team to confidently build, evaluate, and ship AI experiences.
• Drive technical and organizational decisions that improve the scalability, reliability, and adoption of the AI Platform, empowering engineers to own architecture and technical solutions.
• Build strong cross-functional partnerships and influence engineering strategy to establish AI evaluations as a foundational capability that accelerates AI development across Lattice.
What You Will Bring to the Table
• Experience leading and growing high-performing software engineering teams, with a track record of hiring, coaching, and developing engineers into strong technical leaders.
• Strong technical background leading teams that build AI infrastructure, AI-powered products leveraging Large Language Models (LLMs) and/or AI agents, distributed systems, or developer platforms. You are a highly technical engineering leader who leads by example—contributing to architecture, design reviews, and code reviews, diving into implementation details when needed, and raising the technical bar across the team.
• Experience building enterprise SaaS AI products where quality, trust, reliability, and scalability are critical to customer success.
• Proven ability to lead complex cross-functional initiatives from strategy through execution, partnering effectively with Product, Applied AI, Data Science, and Engineering to deliver business impact.
• Excellent communication and stakeholder management skills, with the ability to create clarity, align teams, and influence technical direction in fast-moving, ambiguous environments.
• A strong product and platform mindset, balancing customer impact, engineering velocity, operational excellence, and long-term technical investments.
• A leadership style grounded in curiosity, humility, ownership, and continuous learning, with a passion for building exceptional engineering teams and delivering high-quality AI products.
Nice to Have
• Experience building AI evaluation frameworks, experimentation platforms, or ML infrastructure.
• Knowledge of statistical experimentation, A/B model testing, offline evaluations, or model benchmarking.
• Familiarity with advanced AI optimization techniques such as Direct Preference Optimization (DPO), Reinforcement Learning from Human Feedback (RLHF
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