Senior AI Solutions Engineer
Crunchyroll, LLC17 days ago
Base Salary
$183k - $229k/yr
Responsibilities
- Embed with Content, Marketing, Product, or other business functions to map workflows and identify meaningful AI opportunities.
- Translate business needs into architecture diagrams, data flows, integrations, tool selections, and build-versus-buy-versus-integrate decisions.
- Design and implement production-grade single-agent and multi-agent systems with planning, tool use, state or memory, escalation, and guardrails.
- Engineer reliability through failure handling, retries, tool-error recovery, hallucination recovery, cost and latency controls, and graceful degradation.
- Build evaluation sets, success criteria, tracing, logging, monitoring, and drift detection for production agent systems.
- Manage stakeholder expectations, surface risks, prevent scope creep, and communicate technical tradeoffs to technical and non-technical audiences.
- Develop internal platforms, SDKs, reusable components, and tooling that other teams can adopt.
- Support the ongoing operation and maintenance of solutions after handoff.
Requirements
- 6+ years of software engineering experience, including at least 3 years building applied AI or agentic solutions in production.
- Demonstrated experience designing, building, and shipping reliable tool-using agentic systems that plan, call tools or APIs and MCP servers, and complete multi-step tasks.
- Experience owning reliability engineering, including failure handling, human-in-the-loop controls, guardrails, and cost and latency management.
- Experience building internal platforms, SDKs, or tooling adopted by other teams, with strong design, documentation, and usability.
- Strong Python skills and command of agentic frameworks, tool or function calling, orchestration, state or memory management, prompt and context engineering, RAG architectures, vector databases, LLM APIs, structured outputs, and system integrations.
- Ability to deliver AI solutions end-to-end from problem definition and architecture through implementation.
- Sound judgment about whether to use AI and which approach to use, including agents, RAG, classical ML, or automation.
- Proven ability to work directly with non-technical stakeholders and manage expectations in ambiguous, early-stage environments.
- Preferred experience with multi-agent systems, planner-executor patterns, specialized-agent coordination, and agent-to-agent or protocol-based interoperability.
- Preferred experience in embedded, consultative, or cross-functional roles and workflow analysis or process mapping.
- Preferred experience evaluating and observing agent or LLM systems using tools such as Datadog, LangSmith, or Langfuse.
- Media, entertainment, streaming, or consumer technology experience is advantageous.
- Exposure to AI governance and security review processes, including tool permissions, prompt injection, data handling, and autonomous-action safety, is preferred.
Benefits
- Flexible time-off policies.
- Medical, dental, vision, short-term disability, long-term disability, and life insurance.
- Health Savings Account and healthcare and dependent-care Flexible Spending Account programs.
- 401(k) plan with employer match.
- Employer-paid commuter benefit.
- New-parent support program.
- Pet insurance and some pet-friendly offices.
- Hybrid work arrangement is indicated by the posting.
- Compensation includes a salary and potential performance bonus paid annually.
Tech Stack
DatadogPython
Categories
Solutions Engineering