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.