Software Engineer, Agentic Runtime
Glean Work is hiring a Software Engineer, Agentic Runtime in Mountain View, United States. It pays $180k-$210k a year and Level rates it ; you can apply on Level.
AI in this role
- 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.
- 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, Javascript, Typescript, 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., OpenTelemetry), 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.
- This role is hybrid (4 days a week in our Mountain View office)
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How we rate this
Software Engineer, Agentic Runtime at Glean Work rates 85 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. Open the description and count.
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
- This job starts at
- $180k
- Typical software engineer job
- $168k
This posting starts 7% above the typical software engineer job. 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?
- Walk me through how you've used OpenAI in your day-to-day work.
- What are the limits of Anthropic that you've run into, and how did you work around them?
- What's a project where you used Gemini hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: AI agents, OpenAI, Anthropic, and Gemini. 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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