AI Platform Engineer, Agentic Engineering

BrainCo

$130K — $180K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of production experience building backend systems.
  • Proficient in Python, TypeScript, Go, or Rust.
  • Strong understanding of distributed systems fundamentals.
  • Experience designing and operating APIs that other engineers rely on.
  • Demonstrated success building infrastructure or developer-facing services.
  • Intuitive understanding of developer experience and maintainability.
  • Familiarity with cloud-native technologies like Kubernetes.

Responsibilities

  • Own and manage foundational LLM usage across the company.
  • Design frameworks for sandboxing, orchestration, and auditing.
  • Address complex challenges such as prompt injection defenses.
  • Create resource management models and observability solutions.
  • Integrate AI-assisted development into platform operations.
  • Build systems to allow teams to run agents safely and reliably.
  • Oversee the entire lifecycle of projects from architecture to deployment.

Benefits

  • Competitive salary plus equity
  • Daily lunches
  • Commuter benefits
  • 401(k)
  • Medical, Dental, and Vision insurance
  • Unlimited PTO
Full Job Description
About the role:

You'll join the team that builds and enables agentic workflows across Brain Co. For every engineer, operator, and business team internally, and for the production AI systems we deploy to governments, healthcare systems, and critical industries. This is a platform role at the center of the company's agent-first strategy: you'll build foundational systems used by every engineering team, and the bar is product-grade because the entire company depends on them.

What you'll work on:
  • Own the foundations of how LLMs are used across the company: cost visibility and controls, data privacy, identity and access, routing, and the security posture around all provider traffic.
  • Design the sandboxing, orchestration, audit, and guardrail layers that product teams build their agents on, so verticals don't need to invent their own abstraction.
  • Solve the hard problems: prompt-injection defenses, scoped credentials, kill switches, multi-tenant isolation (including VM-level pod isolation), and runaway-cost controls.
  • Design the orchestration, isolation, and resource models that make this viable: cold-start vs. always-on tradeoffs, credential and token lifecycle, fan-out and fan-in patterns, fairness and quota enforcement across tenants, and the observability needed to debug at that volume.
  • Make AI-assisted development a first-class platform layer: coding agents that review and ship code, automate CI, refactor at scale, and run as background workers across the codebase, together with the canonical scaffolding and guardrails that govern them.
  • Build the systems that let every team; engineering, operations, and the business, run their own agents reliably and safely against the tools they already use, with the right credentials, scheduling, memory, and audit underneath.
  • End-to-end ownership: architecture, implementation, rollout, observability, on-call, and iteration based on internal user feedback.
  • Partner closely with security, infrastructure, and product teams to make agent deployments safe by default.


You Might Be a Great Fit If You...
  • Have 5+ years building backend systems in production, with deep proficiency in at least one of Python, TypeScript, Go, or Rust.
  • Bring strong fundamentals in distributed systems: consistency, idempotency, retries, failure modes, queueing, scheduling.
  • Have designed and operated APIs and services that other engineers depend on.
  • Have a proven track record building shared infrastructure, internal platforms, or developer-facing services that real users adopted.
  • Have strong intuition for developer experience, long-term maintainability, and where to draw abstraction boundaries.
  • Are comfortable owning the full lifecycle: writing the design doc, shipping the MVP, hardening it, and driving adoption across the company.
  • Have owned services with real uptime and operational responsibility, and are comfortable with observability stacks, incident response, and SLOs.
  • Bring cloud-native experience: Kubernetes, infrastructure-as-code, OAuth/OIDC, secrets management.


Ways you might stand out:
  • Experience building or operating LLM infrastructure: gateways, inference systems, prompt routing, cost attribution, evaluation harnesses.
  • Experience with agent frameworks, tool-use systems, or sandboxed code execution.
  • Security instincts around prompt injection, supply-chain risk in agent ecosystems, and credential scoping for autonomous systems.
  • Background in multi-tenant, regulated, or government deployments (HIPAA, SOC2).
  • Open-source contributions to AI infrastructure, agent tooling, or developer platforms.


Why Join Us
  • Collaborate with industry veterans from Tesla, DeepMind, Databricks, and more
  • Accelerate your career with ownership based on impact, not tenure
  • Earn competitive compensation + meaningful equity in a high-growth company
  • Thrive in a culture built on speed, curiosity, and impact


Benefits
  • Competitive salary plus equity
  • Daily lunches
  • Commuter benefits
  • 401(k)
  • Medical, Dental and Vision
  • Unlimited PTO

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