Software Engineer, Evals

Reposted 6 Days Ago
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Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Mid level
Artificial Intelligence • Software • Generative AI
The Role
Build and own large-scale evaluation pipelines and observability infrastructure to measure and improve AI assistant and agent quality. Design scalable, secure, cost-efficient distributed systems for evals, trace processing, telemetry, dashboards, and integration with ML and product workflows.
Summary Generated by Built In
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 - 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 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.  

Skills Required

  • 4+ years software engineering experience building backend systems, infrastructure, distributed systems, or data platforms
  • Strong coding skills in Go, Python, Java, C++ or similar languages
  • Comfortable working with distributed data pipelines, production services, observability systems, or cloud-native infrastructure
  • Analytically rigorous; able to ensure metrics reflect real user experience
  • Experience with LLM applications, evals, tracing, data warehouses, workflow orchestration, or ML infrastructure
  • Willingness to work in customer-focused, cross-functional environments
  • In person in Bangalore, India
  • Mentoring other engineers and contributing to technical design/culture

Glean Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Glean and has not been reviewed or approved by Glean.

  • Healthcare Strength Healthcare coverage includes employer-provided medical, dental, and vision across U.S. roles. Descriptions of benefits and third‑party listings characterize core health offerings as solid.
  • Equity Value & Accessibility Equity is widely offered via stock options and highlighted as a core part of total rewards. Engineering packages are portrayed as particularly competitive when equity value is considered.
  • Leave & Time Off Breadth Time off includes flexible PTO and a company‑wide winter break. Parental leave is described as generous in public listings, though specifics are not consistently published.

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The Company
HQ: Palo Alto, CA
224 Employees
Year Founded: 2019

What We Do

Glean searches across all your company’s apps to help you find exactly what you need and discover the things you should know. 🔍 AI-powered workplace search. 💡 Personalized results and knowledge discovery. ⚡ Easy to use, ready to go— right out of the box.

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