Forward Deployed Engineers at Luma build systems based on customer workflows, defining problems and delivering production solutions using Luma's models and APIs.
About Luma
What You’ll Do
Raise the Bar
Who You Are:
What Sets You Apart
Compensation
A new class of intelligence is emerging, systems that understand and generate the world across video, images, audio, and language. Building multimodal AGI is not just a research problem. It’s a full-stack engineering problem, spanning training systems, inference, product architecture, and the tight feedback loops between them.
When a new technological wave begins, the highest leverage place to be is at the foundation. Not at a startup wrapping someone else’s API. At the company building the models themselves.
The frontier is not incremental improvement. These models are replacing entire categories of software and enabling entirely new ones.
At Luma, we are:
- A leading multimodal AI research lab, having built one of the world’s strongest video generation models (Ray-3.14).
- Pushing beyond video toward the next generation of multimodal general intelligence models.
- Operating at a scale few companies can match, with the compute and resources to support frontier research ($900M Series C).
- Focused on the creative domain, where multimodal systems can have immediate real-world impact.
- Shipping tightly integrated products that turn research breakthroughs into tools creators actually use.
We’re still early. The playbook is not written. A single exceptional engineer can reshape how the company operates.
Where You Come In
Forward Deployed Engineers turn what our models can do into things customers actually rely on. You embed with a customer, learn their workflow, define the problem with them, and build the system that solves it — in production, with their data, with their constraints. You own the relationship and the code. When something is missing in our platform, you build around it. When the same gap shows up across customers, you work with R&D to turn that pattern into product. This is engineering at the edge, where ambiguity is the default and "what should we build?" is yours to answer.
This role is built for people who have already operated as the single point of ownership for a hard problem — and want to keep doing that, with much better tools.
You may have been:
- A technical founder — you built the product, talked to the first customers, made the calls, and shipped. You miss the pace and the autonomy more than you miss running a company.
- An engineer who became the customer's engineer — the one who flew out, sat in their office, and rebuilt their workflow because the standard product didn't fit.
- A consultant or architect who codes for real — you didn't just diagram the system, you wrote it.
- A builder with a customer instinct — strong technical foundation, a track record of personal projects with real users, and a pattern of identifying problems and moving on them without waiting.
What ties these together: you've made the call yourself, you've shipped against ambiguity, and you know the difference between "delivered" and "actually used."
- Work directly with customers to understand their workflows, constraints, and goals.
- Define the problem — there is no PRD waiting for you.
- Build production systems on Luma's APIs, models, and internal tools.
- Prototype, ship, iterate, and maintain systems that customers depend on inside of real environments with real data.
- Own projects end-to-end, from first conversation to deployed system.
- Identify the patterns worth productizing and feed them back to platform and R&D.
FDEs leverage AI to accelerate implementation, but the core of the role is engineering judgment — knowing what to build, how to structure it, and how to make it work reliably in messy real-world environments. Breadth, product intuition, and customer empathy matter more here than narrow specialization. We're not looking for unicorns; we're looking for builders who can hold all three.
- Bachelor's degree in Computer Science or equivalent practical experience
- 2+ years of professional software engineering experience
- Strong proficiency in at least one general-purpose language (Python, TypeScript, Go, or similar)
- Experience building and shipping software end-to-end
- Ability to work across the stack and learn unfamiliar systems quickly
- Ability and interest to travel as needed to client sites
- A track record of shipping real systems with real users, not just completing assigned tasks.
- High agency and strong prioritization skills — you can figure out the core problem and move.
- Comfort defining your own path when there isn't one.
- Evidence of working directly with customers or users, and translating what you heard into what you built.
- Clear communication, including explaining a technical decision to a non-technical stakeholder.
The base pay range for this role is $200,000 – $325,000 per year.
About LumaLuma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.
We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.
Similar Jobs
Artificial Intelligence • Enterprise Web • Software • Design • Generative AI
Build and deploy production-grade agentic workflows for enterprise customers using Webflow APIs, CMS, AI capabilities, and external integrations. Design safeguards, observability, rollback paths, and permission boundaries; support live web properties at scale; collaborate with sales and engineering on complex deployments; and convert customer implementation learnings into reusable architecture blueprints and platform improvements.
Top Skills:
AIAPIsCSSData PipelinesHTMLJavaScriptLlm OrchestrationN8NWebflow ApisWebflow CmsWorkflow Automation
Artificial Intelligence • Software • Cybersecurity
Build customer-embedded solutions for Origin’s AI observability platform. Investigate customer traces and operational data using SQL, ClickHouse, APIs, and MCP tools; develop dashboards, integrations, workflows, prototypes, and production code; lead technical discovery; and translate field insights into reusable product capabilities. The role requires close collaboration with enterprise engineers, security teams, AI platform teams, and executives, with travel of up to approximately 20%.
Top Skills:
APIsAWSAzureClickhouseDockerGCPJavaScriptKubernetesMcpPythonReactRustSQLTerraformTypescript
Healthtech
Embed with clinical, product, and operations teams to deliver production AI features end to end. Build agentic systems using RAG, tool calling, MCP, and orchestration; establish evaluations, validation standards, monitoring, and governance; deploy solutions on the shared AI platform; and create reusable templates and tools. Partner with stakeholders in regulated healthcare environments while improving organizational AI fluency.
Top Skills:
Agent OrchestrationAmazon BedrockAPIsAWSEvaluation HarnessesFunction CallingMcpModel ServingPrompt GuardrailsPythonRagTool Calling
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.


