Software Engineer, Evals
Glean Work is hiring a Software Engineer, Evals in Bengaluru, India. Level rates it ; you can apply on Glean Work.
Level's read on this job
- Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include LLM, Python and AI agents.
- Level classifies it as a mid-level role.
- Level lists 130 other open roles at Glean Work.
AI in this role
Build evaluation pipelines, quality evalsets, and LLM-powered judges to measure and improve AI assistant and agent performance.
About the Team
Building a great AI assistant is only half the battle; knowing whether it is actually great is the other half. The Evals & Observability team owns the measurement and quality layer that makes Glean’s Assistant and Agents reliably better over time: evaluation pipelines, quality evalsets, LLM-powered judges, agent observability, and the tooling engineers use to understand what changed and why.
This is a rare opportunity to work at the intersection of distributed systems, data infrastructure, applied AI, and product quality. You will help build the systems that decide whether new models, prompts, retrieval strategies, and agent workflows are ready to ship to enterprise customers.
About the Role
We are looking for backend and infrastructure engineers in Bangalore to build the platforms that measure, explain, and improve AI quality at scale. You will own core systems for running large-scale evaluations, processing traces, powering observability workflows, and giving engineers clear signals about assistant and agent behavior — including how Glean evaluates frontier model releases and the latest open-source model drops before they shape customer-facing AI experiences.
This role is ideal for someone who loves building reliable distributed systems, cares deeply about product quality, and wants their infrastructure work to directly shape how AI products are shipped. You will work on systems that need to be scalable, secure, permissions-aware, fast, and cost-efficient.
You will
- Design and build large-scale evaluation pipelines that measure assistant and agent quality across thousands of real user and synthetic workflows.
- Evaluate frontier model releases and the latest OSS model drops, building the infrastructure and quality signals that help Glean understand regressions, tradeoffs, and launch readiness.
- Build agent observability infrastructure, including trace enrichment, durable telemetry pipelines, dashboards, and debugging workflows that make AI behavior inspectable.
- Own backend systems from architecture and design docs through production rollout, reliability, monitoring, and iteration.
- Partner with product, ML, and infrastructure engineers to make evals a first-class part of how Glean ships AI features.
- Improve the quality loop by connecting eval results, customer feedback, regression analysis, and engineering workflows into concrete product improvements.
- Build systems that balance speed, reliability, enterprise security, and cost across modern cloud-native environments.
- Mentor other engineers, raise the bar for technical design, and help shape the engineering culture of Glean’s Bangalore AI quality team.
About you
- You have 6+ years of software engineering experience building backend systems, infrastructure, distributed systems, or data platforms.
- You have strong coding skills in Go, Python, Java, C++, or similar languages, with an emphasis on reliability, scale, and well-tested components.
- You are comfortable working with distributed data pipelines, production services, observability systems, or cloud-native infrastructure.
- You are analytically rigorous and care about whether metrics reflect real user experience, not just whether dashboards look good.
- You enjoy customer-focused, cross-functional environments and are willing to take on whatever is most impactful for the company.
- You care deeply about quality, both in the systems you build and in the AI product you help measure and improve.
- Experience with LLM applications, evals, tracing, data warehouses, workflow orchestration, or ML infrastructure is a strong plus.
Location:
- This role is in person in Bangalore, India
Compensation & Benefits:
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 are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
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
Software Engineer, Evals 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.
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
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software 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?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where evaluation was part of your work. What did you do?
- Tell me about a project where observability was part of your work. What did you do?
- Tell me about a project where software engineering was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Machine learning, Evaluation, Observability, and Software Engineering. 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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