Deployment Strategist

About the Role

Longitude Labs is hiring a Deployment Strategist to join as an early builder at a fast-growing model infrastructure company working with the world’s leading AI labs.

As a Deployment Strategist, you will own end-to-end workflows focused on improving the deployment of frontier models in domains that are important for human work. You will work at the intersection of domain expertise, model behavior, and operational execution: identifying high-value workflows, translating them into rigorous model improvement programs, and building the systems needed to deliver them at scale.

The ideal Deployment Strategist combines a technical foundation with strong judgment about how AI can be deployed across domains. They are technically fluent, operationally excellent, and comfortable turning ambiguous problems into high-quality execution. This is a role for someone who can work closely with researchers, experts, and internal teams to build the next generation of training data and evaluations for frontier AI.

You Will

• Own data labeling programs end to end, turning expert knowledge into the training signal that makes AI models genuinely useful in real-world work

• Work at the frontier of AI deployment, figuring out what the best models still get wrong and building the data that fixes it

• Translate messy, expert-level workflows into labeling tasks sharp enough for a contributor to nail and a model to learn from

• Partner with leading researchers and domain experts to set the quality bar for model reasoning

• Hunt down model failure modes and quality gaps, then turn them into sharper guidelines and better data

• Build the systems, pipelines, and tooling that let world-class labeled data ship reliably and at scale

• Recruit and lead a network of expert contributors who care about getting it right

• Own delivery start to finish: scope, throughput, quality, timelines, the whole thing

What You’ll Bring

• 0-2 years of experience working in tech, consulting, finance, or a similar field

• A STEM degree (minor is fine) or technical work experience – analytics, economics, computational finance, etc. are all acceptable

• Operationally intensive experience in a professional role or building and running a venture or organization

• High level of comfort using AI tools

• Comfort working in ambiguity, moving fast, and making good tradeoffs

• Excitement to lead work at the intersection of operations, engineering, and product

Nice to Have

• Former founder or experience at a fast-paced startup

• Experience in forward-deployed engineering, deployment strategy, or solutions, sales, or customer engineering

• A mix of technical and business experience (i.e. comp sci degree + consulting experience)

• Domain expertise in finance, life sciences, materials science, cybersecurity, or another specialized field

• Leadership experience in organizations, teams, or leadership programs

Compensation

At Longitude Labs, total compensation for eligible roles includes base salary, equity, a discretionary performance bonus, and benefits. The salary range listed for this role reflects our target minimum and maximum for new hires and may span more than one career level. Where an offer lands within that range depends on factors such as work location, job-related skills and experience, qualifications, and how you perform during the interview process.

Eligible employees may also receive equity, subject to approval by our Board of Directors. Your recruiter can walk you through the range for your location and confirm equity eligibility as you move through the process.

We believe a well-supported team does its best work. Our benefits include fully covered health, dental, and vision insurance, a 401(k) with employer match, a monthly wellness stipend and unlimited PTO.

Please reference the Work Location and Schedule section for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in San Francisco and New York is:

$180,000 – $200,000 USD

Work Location and Schedule

Full time, New York or SF (in office 4+ days per week),