Jobs
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Home Office Stipend
•Learning Budget
•Mental Health
•Free Meals
•Healthcare
•401k
•Equity
•Home Office
•Learning
•Mental Health
•Meals
Required Skills
Python
Go
Java
C++
Distributed Systems
Kubernetes
Cloud Platforms
Observability
Debugging
About Glean:
Founded in 2019, Glean is an innovative AI-powered knowledge management platform designed to help organizations quickly find, organize, and share information across their teams. By integrating seamlessly with tools like Google Drive, Slack, and Microsoft Teams, Glean ensures employees can access the right knowledge at the right time, boosting productivity and collaboration. The company’s cutting-edge AI technology simplifies knowledge discovery, making it faster and more efficient for teams to leverage their collective intelligence.
Glean was born from Founder & CEO Arvind Jain’s deep understanding of the challenges employees face in finding and understanding information at work. Seeing firsthand how fragmented knowledge and sprawling SaaS tools made it difficult to stay productive, he set out to build a better way - an AI-powered enterprise search platform that helps people quickly and intuitively access the information they need. Since then, Glean has evolved into the leading Work AI platform, combining enterprise-grade search, an AI assistant, and powerful application- and agent-building capabilities to fundamentally redefine how employees work.
About the Role:
The Agents Runtime team builds the low‑latency, reliable, and secure foundation that powers Glean’s AI agents and assistant experiences at scale. You’ll design and operate core runtime services for multi‑turn orchestration, tool calling, model routing, memory, streaming, and safety. You’ll work across distributed systems, production observability, and ML infra integrations to deliver an experience that feels instant, accurate, and trustworthy — while optimizing cost and reliability.
You will:
-
Own impactful runtime problems end‑to‑end — from architecture and design to production launch and ongoing reliability.
-
Build and evolve core services for session lifecycle, streaming responses (e.g., gRPC/WebSockets), structured tool execution, memory/state, and policy/guardrails.
-
Design for performance, correctness, and cost: reduce p50/p95 latency, improve tail behavior, and optimize token/tool budgets.
-
Integrate with leading LLM providers (e.g., OpenAI, Anthropic, Google Gemini) and internal evaluation frameworks to improve quality and predictability.
-
Harden the platform with fault isolation, retries, timeouts, circuit‑breaking, backpressure, and graceful degradation.
-
Instrument deep observability (tracing, metrics, logs) and create playbooks/SLOs for high availability and on‑call excellence.
-
Collaborate closely with product, quality, and application teams to prioritize the most impactful roadmap investments.
You are:
-
3+ years of software engineering experience building production distributed systems or cloud‑native applications.
-
BS/BA in Computer Science or related field, or equivalent practical experience.
-
Strong coding skills in at least one of: Python, Go, Java, or C++, with a focus on reliability, performance, and tests.
-
Product‑minded: you prioritize customer impact, clear SLAs/SLOs, and pragmatic iteration.
-
Ownership‑driven with a positive, proactive attitude; comfortable leading projects or learning from battle‑tested engineers.
-
Experience operating services on Kubernetes and at least one major cloud (e.g., GCP, AWS, or Azure).
-
Familiarity with event/streaming systems (e.g., Pub/Sub, Kafka), caching (e.g., Redis), and data stores for low‑latency paths.
-
Practical understanding of LLM/agents building blocks: tool/function calling, structured outputs, streaming, and model selection/routing.
-
Strong observability and debugging skills: tracing (e.g., Open Telemetry), metrics, dashboards, and production forensics.
-
Background in one or more areas is a plus: policy/guardrails, multi‑tenant isolation, rate‑limiting, concurrency control, cost optimization.
Location:
- This role is hybrid (3-4 days a week in one of our SF Bay Area offices)
Compensation & Benefits:
The standard base salary range for this position is $170,000 - $265,000 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 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.
#LI_HYBRID
Total Views
0
Apply Clicks
0
Mock Applicants
0
Scraps
0
Similar Jobs

Research Engineer
Pika Labs · Palo Alto HQ

Forward Deployed Engineer, Applied AI
Anthropic · London, UK

Senior Software Engineer - .NET Engineering
Microsoft · Czech Republic, Prague, Prague

Lead Project Engineer - Xbox Games Technology Group - The Coalition
Microsoft · Canada, British Columbia, Vancouver

Research Engineer - User Identity Knowledge Graph
Netflix · USA - Remote; Seattle,Washington,United States of America; New York,New York,United States of America; Los Angeles,California,United States of America; Los Gatos,California,United States of America
About Glean

Glean
Series BA free, personalized, intelligent news feed that helps you find the best events, apps, and articles on your Android or iOS phone
1-50
Employees
New York
Headquarters
$2.2B
Valuation
Reviews
3.7
2 reviews
Work Life Balance
4.0
Culture
3.0
Career
4.0
Management
3.5
65%
Recommend to a Friend
Pros
Flexible hours and hybrid working
Strong commitment to Lean philosophy
Good learning opportunities
Cons
Too many meetings
Less favorable treatment for non-native English speakers
Language discrimination issues
Salary Ranges
38 data points
Junior/L3
Junior/L3 · Solution Architect
0 reports
$62,409
total / year
Base
-
Stock
-
Bonus
-
$53,048
$71,770
Interview Experience
2 interviews
Difficulty
3.5
/ 5
Duration
14-28 weeks
Offer Rate
50%
Experience
Positive 50%
Neutral 0%
Negative 50%
Interview Process
1
Final Interview
2
Final EM Interview
News & Buzz
Glean AI Review 2026: Features, Pricing, and Alternatives - Cybernews
Source: Cybernews
News
·
5w ago
Glean Technologies
Got an offer at Glean for a Solutions Architect. Product is really interesting, but I wonder what the longevity of it will be and potential exit opportunities. Any inputs?
·
6w ago
·
24
·
80
[Lewenberg] TSN can confirm that Toronto appears willing to part with some combination of Immanuel Quickley, Jakob Poeltl and RJ Barrett, or at least that’s the impression that rival teams have gleaned from exploratory discussions.
> TSN can confirm that Toronto appears willing to part with some combination of Immanuel Quickley, Jakob Poeltl and RJ Barrett, or at least that’s the impression that rival teams have gleaned from exploratory discussions. That tracks, both because the Raptors would need to include one or two of t
·
6w ago
·
170
·
183
Is there anything that can be gleaned from someone who is really good at boardgames?
I know someone who is really good at boardgames. It doesn't matter if they've played the game before or not. They're able to amass SO many victory points and I'm just kind of in awe. They just "get" the game. I'm not even sure how they're able to be so effective. So, I'm just wondering if there
·
8w ago
·
273
·
208