Software Engineer, Agents

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Onsite From the posting source checked Jun 20, 2026

In-office days

5 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Software Engineer, Agents San Francisco | OnSite | New York City | United States WHAT WE'RE BUILDING In 2026, we're on the verge of an "infinite software crisis." How will we support, maintain, and operate the explosion in application development? Our answer is Sazabi: the AI-native observability platform for fast-moving engineering teams. Sazabi gives teams a single place to ask questions about their production systems in plain language, automatically visualize what's happening, and get to the root cause 10x faster. No tedious instrumentation. No dashboard configuration. No alert tuning. Just answers. We're backed by tastemakers from the world's top AI companies: Vercel, Graphite, Daytona, Browserbase, LangChain, Mastra, Replit, and more. WHAT YOU'LL DO - Build and iterate on the core AI agents that power Sazabi - Design systems for anomaly detection, root cause analysis, and automated debugging - Work on prompt engineering, tool use, and agent orchestration - Improve reliability, latency, and correctness of AI-driven workflows - Experiment rapidly with new models, frameworks, and techniques - Translate messy real-world production issues into structured AI workflows WHAT WE'RE LOOKING FOR - Strong experience working with LLMs in production (agents, RAG, tool use, etc.) - Deep curiosity about how and why AI systems fail-and how to fix them - Ability to prototype quickly and iterate based on real-world feedback - Strong engineering fundamentals (this is not just prompt hacking) - Comfort operating in a fast-moving, experimental environment - Bonus: experience with observability, debugging systems, or developer tools OUR TECH Our stack is

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