Senior Software Engineer, Applied AI

Bot Auto; Houston (TX); On-site; USD 160,000 - 220,000; Full time

Benefits offered by this job

Health insurance

Job summary

Bot Auto is hiring a Senior Software Engineer, Applied AI to architect, build, ship, and operate production-grade AI and agentic systems across Bot Auto. You will own the system end-to-end across backend services, full-stack apps, databases, and integration with enterprise tools.

The role focuses on probabilistic agent reasoning, tool calling, memory, and guardrails, while ensuring security, scalability, and cost efficiency in production environments.

Qualifications

• 6+ years of relevant professional software engineering experience or equivalent production systems experience.
• Hands-on experience architecting, building, shipping, and operating production-grade AI agentic applications or workflows.
• Strong backend and full-stack engineering capability across services, APIs, databases, and state.
• Proficient in Python and at least one modern language (TypeScript/JavaScript or Go).
• Deep understanding of distributed systems, data modeling, transactions, and production design.
• Solid knowledge of cloud infrastructure, containers, CI/CD, observability, security, and operations.
• In-depth understanding of LLM/agent systems, tool orchestration, memory, and guardrails.
• Experience handling production issues like nondeterministic failures, latency, and cost trade-offs.

Responsibilities

• Own architecture and end-to-end implementation of production agentic products and workflows.
• Design boundaries between deterministic software, workflow engines, databases, and probabilistic reasoning.
• Build and review backend services, APIs, full-stack apps, and operator tools for agentic workflows.
• Design agent orchestration, tool contracts, memory, context, and failure recovery.
• Design production data architecture, including schemas, caching, and event systems.
• Integrate AI systems with enterprise tools and data platforms with proper permissions and auditability.
• Collaborate with infrastructure on cloud, containers, CI/CD, observability, security, and cost.
• Create reusable engineering patterns and translate high-value workflows into reliable products.

Skills

Backend development

Full-stack development

Python

TypeScript/JavaScript

Go

Distributed systems

Cloud infrastructure

CI/CD

Observability

LLM/agent systems

Tool calling

Performance optimization

Production issue ownership

Tools

MCP

LangGraph

LangChain

LlamaIndex

Temporal

Job description

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.

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.

Compensation

For candidates based in California, the anticipated annual base salary range for this position is $160,000–$220,000. The final base salary will be determined based on factors such as the candidate’s qualifications, relevant experience, demonstrated skills, position level, scope of responsibilities, and work location. This base salary range does not include any applicable bonus, equity, or benefits.