> Markdown version of [/jobs/ext/3571283-forward-deployed-engineer](https://www.wearedevelopers.com/jobs/ext/3571283-forward-deployed-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer - **Company:** Crunchyroll, Inc. - **Location:** Los Angeles, CA, United States - **Experience:** Expert - **Salary:** $183,400.0 - $229,200.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Security, Data Systems, Fault Tolerance, Python (Programming Language), Machine Learning, Software Engineering, Data Streaming, Systems Integration, Datadog, Data Logging, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Langfuse — LLM Observability and Analytics Platform, Event Driven Architecture, Build Management, LangSmith, Low Latency, Drift Detection, Human in the Loop - **Published:** October 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d5f7a3a549c6c98f ## About the Role * 6+ years of software engineering experience, including significant recent experience building and shipping applied AI or LLM-powered systems in production. * Demonstrated experience designing, building, and deploying AI systems that interact with APIs, enterprise systems, data sources, or external tools to complete multi-step tasks. * Strong Python skills and deep experience with modern LLM application development, including tool and function calling, orchestration, prompt and context engineering, structured outputs, RAG, model APIs, state management, and enterprise integrations. * Experience taking AI solutions end-to-end, from an ambiguous problem statement through architecture, prototyping, implementation, deployment, and iteration. * Experience engineering AI systems for reliability, including failure handling, human-in-the-loop controls, guardrails, permissions, monitoring, cost management, and latency management. * Strong technical judgment on when to use an agent, RAG, classical ML, automation, or conventional software, including the discipline to avoid unnecessary complexity. * Proven ability to work directly with non-technical stakeholders, understand how their work actually happens, and translate business needs into practical technical solutions. * Strong product and business judgment. You can distinguish an interesting technical problem from a problem worth solving. * Comfort operating in ambiguous, early-stage environments where you are expected to define the problem as much as solve it. * The ability to move between rapid experimentation and production engineering, knowing when speed matters and when reliability, security, and scale matter more., * Experience in a forward-deployed, embedded, solutions engineering, applied AI, or highly cross-functional engineering role. * Experience building tool-using or agentic systems that plan and execute multi-step workflows. * Experience with APIs, MCP, event-driven systems, enterprise SaaS integrations, and internal data systems. * Experience building internal platforms, SDKs, reusable tooling, or shared components adopted by other engineering teams. * Experience evaluating and observing LLM or agent systems, including eval design, tracing, monitoring, and drift detection using tools such as Datadog, LangSmith, Langfuse, or similar platforms. * Experience designing multi-agent systems, planner/executor architectures, specialized agents, or other orchestration patterns where they are appropriate. * Familiarity with workflow analysis and process mapping, particularly in complex operational environments. * Exposure to AI governance, security, privacy, and legal review processes, including risks related to data access, permissions, prompt injection, tool use, autonomous actions, and sensitive information. * Experience in media, entertainment, streaming, consumer technology, or another environment with complex content and operational workflows. Familiarity with areas such as localization, marketing operations, content operations, customer support, rights management, or commerce is a plus. ## Description * Embed deeply with business teams. Sit alongside them as work happens, map the real workflow rather than the documented one, and understand the pain points, decisions, systems, and handoffs that shape how work gets done. * Identify where AI can create meaningful business value. Start with the problem, not the technology, and be willing to conclude that AI is not the right answer. * Determine the right technical approach for each problem, whether that is an agentic system, generative AI, RAG, classical ML, deterministic automation, or a simpler software solution. * Translate ambiguous business problems into clear technical plans, including architecture, data flows, integration points, permissions, tool usage, success criteria, and build vs. buy vs. integrate decisions. * Prototype quickly to test whether an idea works before over-engineering it. Know when to build something in days to learn and when a problem warrants production-grade infrastructure. * Design and build reliable AI systems end-to-end, including tool use, orchestration, context and prompt engineering, state and memory, structured outputs, APIs, enterprise integrations, and human-in-the-loop workflows. * Engineer for the real world, not the demo. Anticipate failure modes, tool errors, hallucinations, retries, permission boundaries, latency, cost, security constraints, and graceful degradation. * Build evaluations and observability from the start. Define task-level success criteria and eval sets, and instrument tracing, logging, monitoring, cost, quality, and drift so performance is measurable in production. * Define the expected business outcome before you build and measure whether the solution actually improves the workflow after launch. * Work directly with business and technical leaders, translating between business needs and technical reality, setting clear expectations, surfacing risks early, and keeping stakeholders aligned as the solution evolves. * Stay close to users after launch. Observe how solutions perform in real workflows, iterate based on usage and feedback, and partner with the broader AI Enablement team on adoption and change management. * Build for handoff and scale. Establish clear ownership, documentation, monitoring, and maintenance paths so successful solutions can transition to the appropriate long-term owner. * Create reusable components, patterns, tools, and learnings that make future AI solutions faster and easier to build across Crunchyroll., The Executive Office enables enterprise alignment, executive execution, and strategic acceleration, working to keep Crunchyroll's highest-priority work moving with clarity and speed. ## Related Videos - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [Building a Multi-Agent Orchestration Engine That Actually Follows the Rules](https://www.wearedevelopers.com/videos/100159-building-a-multi-agent-orchestration-engine-that-actually-follows-the-rules) - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [The Memory Leak That Ate Our Cluster: A Postmortem](https://www.wearedevelopers.com/videos/2057-the-memory-leak-that-ate-our-cluster-a-postmortem) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Unleash the power of 5G in your code: transform your apps](https://www.wearedevelopers.com/videos/1567-unleash-the-power-of-5g-in-your-code-transform-your-apps) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [ I Gave a Video Editor More Autonomy Than a Trading Bot. On Purpose.](https://www.wearedevelopers.com/magazine/773-i-gave-a-video-editor-more-autonomy-than-a-trading-bot-on-purpose) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)