At Scale, we build the AI systems behind some of the country's most important decisions. On the Public Sector Engineering team, you'll embed directly with U.S. government customers, including the Army, Air Force, Joint commands and Intelligence Community, to build and deploy AI applications that support their most critical missions.
This is a hybrid customer-facing engineering role. You'll sit with the people whose problems you're solving, own delivery from first prototype to production, and ship software that customers adopt and rely on in the field. Model performance matters, timelines are urgent, and ambiguity is the norm. Your work directly shapes what Scale's platform can do for the public sector.
What you'll do- Embed with government customers to understand their mission, scope the problem, and turn it into working software.
- Own delivery end-to-end: design, build, deploy, and maintain solutions at customer sites, from prototype to stable production.
- Build robust backend systems and data integrations that connect customer environments to Scale's platform and back.
- Partner with product and engineering to feed field signals back into the roadmap, so the patterns you build once become capabilities the whole team can reuse.
- Serve as the technical point of contact for customer stakeholders, guiding adoption and maximizing mission impact.
Required
- 5+ years of software engineering experience, ideally in customer-facing, forward-deployed, or government contexts.
- Strong production coding in Python and TypeScript (or comparable modern languages).
- Comfort across the stack, including cloud platforms (AWS, Azure, or GCP), containers, Linux, and networking fundamentals.
- Ability to operate independently in ambiguous, fast-moving environments and make sound trade-offs under pressure.
- An active TS/SCI clearance.
Bonus
- Experience building or deploying systems powered by LLMs or generative models.
- Familiarity with Node and React, Kubernetes and Docker, and Terraform.
- Data engineering background covering ETL pipelines, data modeling, and data governance.
This role requires significant time on-site with customers. Expect 25% travel with up to 50% travel as necessary, and/or relocation to Washington DC or St. Louis.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
