Staff Engineer, Agentic AI

Reposted 2 Months Ago
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Santa Clara, CA, USA
Hybrid
160K-200K Annually
Mid level
Software
The Role
Design, build, and ship production multi-agent LLM systems including orchestration, memory/retrieval, safe write-back to customer systems, evaluations and regression tests, adversarial hardening, LLM model-agnostic integration, and cost/latency/reliability ownership at enterprise scale.
Summary Generated by Built In

LeanData helps the world's fastest-growing companies automate, simplify, and accelerate revenue.

We are looking for a Staff Engineer with experience building Agentic AI systems to help design and ship production multi-agent systems at the core of LeanData's new platform of autonomous agents for go-to-market teams.

This is a Staff-level individual-contributor role with founding-level ownership. You would work closely with engineering and product leadership to define and build the architecture of a sophisticated multi-agent system able to reason over go-to-market data and act reliably at enterprise scale. This a Senior technical position — any engineer can tell a coding agent to build things; we are looking for people who know how to design and deliver production agentic systems that actually work safely when connected to customers' live data systems, and who give deep thought to best-practices for building production agentic systems. We know just about every candidate for this position has built agentic systems — we are going to ask how you made sure the systems you built work.

This role reports to the Director of Engineering - AI and Machine Learning, and is based in our Santa Clara, CA office. You are required to be in office Mondays and Wednesdays each week.

What you'll be doing

  • Designing and building multi-agent systems that are able to work with complex, dirty data structures and varying policies to safely write to mission-critical customer data stores

  • Establish patterns and best practices that help the whole team build better and faster

  • Agent control loops and planning, the orchestration graphs and tools they call, and the coordination, handoffs, state, and durability across agents

  • Build the safe write-back path that applies agent decisions to a customer's live systems without corrupting data

  • Measure, test, and evaluate everything you ship: build the eval cases, rubrics, and regression tests that prove a change made the agent better

  • Guardrails for agentic systems

  • Integrate frontier LLMs behind a model-agnostic abstraction with routing by task, cost, and latency; own the cost, latency, and reliability of your surface, and create the patterns that let the team build agents faster

Requirements

  • 4+ years building production systems, including 2+ years shipping LLM-powered or agentic systems

  • You have shipped customer-facing LLM or agent systems that real users depend on, and can explain how they failed and how you fixed them

  • High agency: you scope, prioritize, and ship without waiting for permission

  • Ability to reason, make decisions, and act in the face of ambiguity

  • Strong, current Python (TypeScript or Go a plus)

  • Hands-on with a modern agent framework / orchestration (e.g. LangGraph or agent SDKs), tool/function-calling, structured outputs, retrieval (RAG), and context/memory management

  • Strong systems-engineering fundamentals (concurrency, distributed systems, statefulness, latency and cost at scale), plus skill debugging deep, non-deterministic failures in multi-step agent traces

Bonus points if you have

  • Experience with Salesforce APIs (Bulk 2.0, Composite, Pub/Sub) or another large, messy enterprise data source

  • A founder or founding-engineer background, or contributions to open-source agent or LLM tooling

Compensation

The salary for this role will be between $160,000 and $200,000 base, plus equity.

Skills Required

  • 4+ years building production systems, including 2+ years shipping LLM-powered or agentic systems
  • Shipped customer-facing LLM or agent systems and can explain failures and fixes
  • Strong, current Python
  • TypeScript or Go
  • Hands-on with modern agent framework / orchestration (e.g., LangGraph or agent SDKs), tool/function-calling, structured outputs, retrieval (RAG), and context/memory management
  • Strong systems-engineering fundamentals (concurrency, distributed systems, statefulness, latency and cost at scale) and debugging non-deterministic multi-step agent failures
  • High agency: scope, prioritize, and ship independently
  • Based in Santa Clara office; in-office Mondays and Wednesdays each week
  • Experience with Salesforce APIs (Bulk 2.0, Composite, Pub/Sub) or another large enterprise data source
  • Familiarity with MCP, A2A, modern eval/observability stack (Promptfoo, Braintrust, Langfuse) and durable execution (Inngest, Temporal)
  • Experience running hundreds or thousands of concurrent agent instances, multi-tenant data isolation (Postgres + RLS), strong security posture for customer data
  • Founder or founding-engineer background or contributions to open-source agent/LLM tooling
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The Company
HQ: Santa Clara, CA
240 Employees
Year Founded: 2012

What We Do

Today’s growth leaders are powering their B2B selling with LeanData, the gold standard in modern revenue orchestration and an essential element of the modern RevTech stack. The LeanData Revenue Orchestration Platform, powered by No-Code Automation, simplifies and accelerates the coordination of all the plays, people, and processes needed to transform buyer signals into buying decisions. With LeanData, revenue teams operate with precision and alignment, taking every change in stride and driving operational excellence that fuels compelling buyer experiences.

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