Full stack developer • san francisco ca
We build infrastructure for Agent Behavior Monitoring (ABM).While traditional observability focuses on logging exceptions and latency, ABM surfaces behavioral anomalies such as instruction drifts a... Show more
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The average salary range is between $ 110,011 and $ 170,452 year , with the average salary hovering around $ 131,743 year .
The average salary range is between $ 97,501 and $ 150,000 year , with the average salary hovering around $ 116,923 year .
About The Company
We build infrastructure for Agent Behavior Monitoring (ABM). While traditional observability focuses on logging exceptions and latency, ABM surfaces behavioral anomalies such as instruction drifts and context retrieval loss in scaled production environments. Hundreds of teams building autonomous agents rely on our platform to understand how their systems are behaving post-deployment. The team has raised $30M+ across two rounds in the past five months.
About the Role
We’re hiring a Full-Stack Engineer to own the product experiences and agent infrastructure that make the agent improvement loop legible and actionable for engineering teams. This is not a role where you implement specs handed down: you will talk to customers, define what to build, build it, and iterate until it is great. The role spans from the data layer to the UI, including the agent swarm interfaces, verification platforms, and the SDK layer that lets developers summon our mid-development. About 30% of the role is customer-facing.
What You'll Own
Shape how our Agent runs large-scale parallel investigations across thousands of production
traces, merging failure modes, tool errors, regressions, and drift signals into a single actionable answer
Build the platform for verifying agent changes: hosted simulated environments for stateful agent evals,
trajectory replay against changed agents, and monitors for unintended behavior
Design how engineers understand long traces, tool calls, decisions, and failures: making a thousand-step
reasoning trajectory legible in minutes
Build the swarm UX so engineers can watch parallel investigations, redirect investigators that go down the
wrong path, and consume findings without reading hundreds of reports
Own the improvement loop: the workflows that turn production trajectories into datasets, judges, and
regression checks so the path from found problem to verified fix feels like one motion
Build and maintain the SDK and terminal-first experience so agent development sessions can summon our agent as a subagent mid-development
Own platform infrastructure: workspaces, roles, permissions, billing, usage, and limits for teams running many
agents across many environments
Requirements
Must-Have
Experience building and scaling end-to-end production systems, from data layer to UI
Hands-on experience building with LLMs or agents, or demonstrable drive to get there fast
Comfort working directly with customers to understand their needs and solve real-world problems
(approximately 30% of the role is customer-facing)
Strong technical problem-solving ability in fast-changing, ambiguous environments
Excellent communication skills: clear, direct, and persuasive across technical and non-technical audiences
Based in San Francisco or willing to relocate; 5 days per week in-person
Nice-to-Have
Prior evals, observability, or agent behavior-monitoring product experience
Strong engineering pedigree from a solid product company (e.g. Roblox, Snapchat, Tesla); top-tier infra
background (e.g. Databricks) is a bonus
Prior forward-deployed or solutions engineering experience
Prior 0-to-1 startup experience as an early hire
Founder background or strong founder-to-be signal
Comfort across the full stack with backend and infrastructure weight
Visa Sponsorship: H-1B, O-1, OPT
NB: We work in person in San Francisco. We're open to sponsoring truly exceptional candidates on a case-by-case basis, but our main scope will be candidates who don't require this.
Compensation
Junior level (3 years experience): $200K
Mid to senior level (3-7 years experience): up to $300K
Exception: exceptional AI-savvy FDE leads can reach $400K on a case-by-case basis
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