Job Overview
Location
Santa Clara
Job Type
Full-time
Category
Software Engineering
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • Design and ship production multi-agent systems that automate go-to-market workflows, including agent control loops, planning, orchestration graphs, and tool-integration layers
- • Build and maintain the safe write-back path that applies agent decisions to customers’ live data systems without risk of data corruption or inconsistency
- • Develop evaluation frameworks with custom test cases, rubrics, and regression tests to measure agent performance and prove improvements from system changes
- • Design agent memory systems including persistent per-account context, pre-computed state, and just-in-time retrieval mechanisms to ensure fast, cheap, and reliable reasoning across thousands of concurrent agent instances
- • Harden agent systems against adversarial inputs such as malformed account names or maliciously crafted notes that could hijack agent behavior or decision logic
- • Integrate frontier large language models behind a model-agnostic abstraction layer, routing tasks by cost, latency, and performance requirements while owning the reliability and cost efficiency of the agent surface
- • Create reusable patterns and abstractions that accelerate the team’s ability to build new agents while maintaining consistency, safety, and observability
- • Own end-to-end delivery of agent systems from concept to production, including debugging deep, non-deterministic failures in multi-step agent traces
- • Collaborate with cross-functional teams to align agent capabilities with go-to-market business objectives and customer data requirements
- • Maintain high standards for system durability, concurrency, and distributed systems design under enterprise-scale loads
- • Ensure multi-tenant data isolation and a strong security posture when handling sensitive customer data within agent memory and execution environments
- • Continuously optimize for latency, cost, and reliability across agent operations, balancing performance with economic efficiency at scale
- • Document system architecture, failure modes, and operational procedures to enable team scalability and knowledge sharing
🎯 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
- • 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
- • High agency: you scope, prioritize, and ship without waiting for permission
🏖️ Benefits
- • Salary between $160,000 and $200,000 base, plus equity
- • Office-based role requiring in-office presence on Mondays and Wednesdays each week
- • Work at the core of LeanData’s new autonomous agents platform for go-to-market teams
- • Opportunity to own founding-level systems with direct impact on enterprise revenue automation
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About LeanData Inc.
LeanData provides revenue operations software that matches leads to accounts, routes prospects, and orchestrates go-to-market workflows for B2B sales and marketing teams. Its cloud platform deduplicates, enriches, and segments data, then applies rule-based routing to ensure timely, accurate handoffs across territories and channels. Built natively on Salesforce, the solution offers native CRM integration, analytics dashboards, and audit trails to improve conversion rates, pipeline visibility, and revenue attribution for mid-market and enterprise organizations.
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