Senior Software Engineer, Applied AI

Bot Auto

$160K — $220K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6+ years of professional software engineering experience or equivalent in building production systems.
  • Hands-on experience with architecting and operating AI agentic applications or workflows.
  • Strong backend and full-stack engineering skills across services, APIs, and databases.
  • Proficient in Python and at least one modern language (e.g., TypeScript, JavaScript, Go).
  • In-depth understanding of distributed systems, data modeling, and event-driven architectures.
  • Solid knowledge of cloud infrastructure and production operations practices.
  • Deep understanding of LLM/agent systems, including orchestration and workflow state.

Responsibilities

  • Own architecture and implementation of production AI agentic products from conception to deployment.
  • Design boundaries between deterministic software, workflows, and probabilistic reasoning.
  • Build and review services and applications supporting agentic workflows.
  • Design orchestration for various workflow states and error handling mechanisms.
  • Create production data architecture and system consistency behavior.
  • Integrate AI systems with internal APIs and enterprise tools while managing permissions and audits.
  • Collaborate on cloud architecture, security, and operational scaling.

Benefits

  • Flexible work arrangements to support work-life balance.
  • Opportunities for professional development and skills training.
  • Access to cutting-edge AI technology and frameworks.
  • Supportive team environment fostering collaboration and innovation.
Full Job Description
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.

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