Software Engineer - AI Enablement
Scale AI is hiring a Software Engineer - AI Enablement in San Francisco, United States. It pays $180k-$225k a year and Level rates it ; you can apply on Scale AI.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 7% above the typical software engineer posting on Level.
- Tools and skills the posting cites include TypeScript, Python and LLMs.
- Level classifies it as a mid-level role.
- Level lists 170 other open roles at Scale AI.
AI in this role
Build full-stack agentic features, backend services, and LLM integrations for enterprise generative AI workflows.
Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems.
We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers.
What we run on is what we sell.
This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions.
If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you.
What You’ll Do
- Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area
- Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms
- Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure
- Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows
- Ship quickly through tight experimentation loops while maintaining high quality and reliability
- Adapt across the stack and learn new tools as needed to solve real problems end-to-end
Ideal Experience
- 3+ years of full-time software engineering experience
- Solid full-stack fundamentals with production ownership of features you've shipped
- Familiarity with LLMs, embeddings, vector databases, or modern AI data products/tools
- Exposure to distributed systems and cloud-based architectures
What We Value
- Strong product intuition and customer empathy
- Entrepreneurial mindset, building and implementing agentic workflows
- Ownership mentality — you see problems through to outcomes
- Comfort collaborating across engineering, product, data science, and applied AI
- Excitement about building agentic systems that make AI genuinely useful in the real world
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.
The base salary range for this full-time position in the location of San Francisco is:$180,000—$225,000 USDPLEASE 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 accommodations@scale.com. 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.
How we rate this
Software Engineer - AI Enablement at Scale AI rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $180k
- Typical software engineer job
- $168k
This posting starts 7% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How have you integrated a large language model into a production application?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a workflow you automated with AI tools, end to end.
- Tell me about a project where full stack was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: LLM Integration, AI agents, AI Automation, Full Stack, and Distributed Systems. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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