AI Engineer - Quality and Post-Training

Glean Work is hiring an AI Engineer - Quality and Post-Training. It pays $200k-$280k a year and Level rates it ; you can apply on Glean Work.

Level's read on this job

Builds AI ●●●● is how Level rates this AI engineer role: the job is building AI systems.
Pay on this posting starts 9% higher than the typical AI engineer posting on Level.
The posting mentions LLMs, Python and AI agents among its tools and skills.
Glean Work has 125 other open roles on Level.
Posted in the last few days.

AI in this role

Build and scale quality, post-training, and evaluation systems for enterprise AI agents and assistants.

llmspython

ai-agentsfine-tuningmachine-learningpost-trainingquality-assurance

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.

About the Role:

The bottleneck in building reliable and useful AI agents isn't writing code anymore. It's knowing what good looks like, measuring it, and steadily closing the gap. Glean is building the next generation of enterprise AI assistants and autonomous agents that reason, plan, and act across complex, multi-step workflows. This role works at the intersection of applied research, quality, and product engineering to make those systems better.

The focus is on quality improvements across Glean's models and agent harnesses. That means hill-climbing with evals, evolving evalsets and agentic verifiers, post-training models for use cases like model routing, and training task-specific models for enterprise workflows. It also means bringing emerging research into the product and working closely with product teams and customers, turning learnings from evals and production usage into better outcomes through quality improvements.

You will:

Use eval results and production traces to improve the entire stack, including the agent harness, model routing, prompts, and retrieval, while weighing quality against latency and cost.
Work on post-training models with supervised fine-tuning (SFT) and preference- or reward-based optimization (e.g., DPO, PPO, GRPO), including generating the data for training.
Build RL environments for simulating enterprise workflows, including relevant evalsets, harness support, and LLM-based verifiers for hill-climbing and for internal and external benchmarking.
Improve the quality of representative evalsets, LLM judges and agentic verifiers, and calibrate them against human graders so the scores can be trusted in release decisions and model training.
Work with product, platform, and research teams across Glean to land quality improvements in production.

About you:

5+ years of industry experience in AI or Machine Learning Engineering.
Hands-on experience post-training LLMs including adapting open-weight models to specialized tasks.
Experience building evals for AI assistant and agent systems, including generating evalsets, LLM-as-a-judge verifiers, calibrating offline and online signals coupled with good judgment about when a metric reflects quality improvements.
Strong coding skills in Python and/or Go (TypeScript is a plus), proficiency in your ML framework of choice, and a track record of shipping production ML systems.
Product-minded, able to turn a vague problem into a concrete experiment, and thrive in a tight-knit, cross-functional team.

Location:

This role is hybrid (4 days a week in our Mountain View or San Francisco office)

Compensation & Benefits: The standard base salary range for this position is $200,000 - $280,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis of gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. #LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy. By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement.
By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement, and I agree to the terms.

How we rate this

AI Engineer - Quality and Post-Training at Glean Work rates 90 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.

Classification

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.

Key facts

AI Engineer - Quality and Post-Training is an open job at Glean Work.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $200k-$280k a year.
The role is based in San Francisco Bay Area.
The job was posted on October 23, 2026.
Seniority: senior.
Applications are handled by Glean Work. Apply on Glean Work

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsFine-tuningMachine learningPost TrainingQuality AssuranceLLMsPython

Also common in AI engineer jobs at this level

AWS Generative AI Azure RAG Google Cloud PyTorch

Pay

This job starts at: $200k
Typical AI engineer job: $184k

This posting starts 9% above the typical AI engineer job. See AI engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where post training was part of your work. What did you do?
Tell me about a project where quality assurance was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI agents, Fine-tuning, Machine learning, Post Training, and Quality Assurance. 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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