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Bot Auto

Senior Software Engineer, Applied AI

Houston, Texas (preferred), or the San Francisco Bay Area; Houston OfficeUnited States
Senior · Software Engineering
POSTED 18 SEPT
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Role
52 days opentrue age
Posted 18 Sept
Pay
$145k–$166kno pay posted
Market p25–p75
$145k–$166k
Houston · n=4 · 365d to 6 Nov
CompanyBot Auto →
25open roles
Opened · 30d
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Closed · 30d
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17,061open · Senior Software engineering
Opened · 7d
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All software engineering
75,165open
All tracked boards · live 9 Nov · n=17,061
TypeScriptJavaScriptPythonDockerLLMsDistributed systems

Company Introduction

At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.

We are seeking a Senior Software Engineer, Applied AI to architect, build, ship, and operate production-grade AI and agentic systems across Bot Auto. This is an engineering-first role for a senior software engineer with proven experience building real AI agentic products or business workflows in production. You should be comfortable owning the system end to end across backend services, full-stack applications, databases, infrastructure, integrations, and modern AI/LLM engineering, while making sound decisions about where probabilistic AI should and should not be used.

Key Responsibilities

  • Own architecture and end-to-end implementation of production agentic products and workflows from problem definition through deployment and operation.
  • Design boundaries between deterministic software, workflow engines, databases, source systems, and probabilistic agent reasoning.
  • Build and review backend services, APIs, full-stack applications, and operator/user-facing tools supporting agentic workflows.
  • Design agent orchestration, tool contracts, workflow state, memory, context, retrieval, approvals, escalation, retries, idempotency, rollback, and failure recovery.
  • Design production data architecture, including relational schemas, state persistence, caching/search, event systems, and consistency behavior.
  • Integrate AI systems with enterprise tools, internal APIs, data platforms, and operational systems while preserving permissions, auditability, and source-of-authority boundaries.
  • Partner with infrastructure teams on cloud architecture, containers, CI/CD, queues, observability, tracing, security, scaling, latency, and cost.
  • Establish reusable engineering patterns and reference implementations; work directly with users to convert high-value workflows into reliable products.

Required Qualifications

  • 6+ years of relevant professional software engineering experience, or equivalent demonstrated experience building and shipping production systems.
  • Demonstrated hands-on experience architecting, building, shipping, and operating production-grade AI agentic applications, products, or business workflows.
  • Strong backend and full-stack engineering capability across services, APIs, databases, application state, and user-facing web applications.
  • Strong programming skills in Python and at least one modern application language such as TypeScript/JavaScript, or Go.
  • Strong understanding of distributed systems, databases, data modeling, transactions/consistency, event-driven architectures, and production application design.
  • Strong working knowledge of cloud infrastructure, containers, CI/CD, observability, security, and production operations.
  • Deep practical understanding of LLM/agent systems, including tool calling, orchestration, context, retrieval, memory, workflow state, human review, guardrails, and failure recovery.
  • Experience owning real production issues such as nondeterministic failures, stale context, tool errors, duplicate actions, permission failures, model regressions, latency, and cost trade-offs.

Preferred Qualifications

  • Experience with MCP, LangGraph, LangChain, LlamaIndex, or equivalent agent/tool orchestration frameworks.
  • Experience with Temporal or another durable workflow engine for long-running, stateful workflows.
  • Experience designing RAG, hybrid retrieval, vector search, graph/knowledge systems, or context-engineering architectures.
  • Experience with eval-driven development, tracing, offline/online evaluation, model/prompt versioning, guardrails, and regression testing.
  • Experience leading technical initiatives across teams; experience in autonomous systems, logistics, robotics, or other mission-critical domains is a plus.
Source · Bot AutoFirst seen 2 NovOriginal ↗