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ML6

Forward Deployed Engineer

ML6 is hiring a Forward Deployed Engineer for a remote role open to applicants in Belgium. Level rates it ; you can apply on ML6.

Level's read on this job

  • On Level's scale, this forward deployed engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include Python, AI agents and applied AI.
  • Level classifies it as a mid-level role.
  • Level lists 14 other open roles at ML6.

AI in this role

Own the last-mile deployment of an enterprise AI platform, building integrations, agentic workflows, and customer-specific solutions.

Python
ai-agentsapplied-aifull-stackcustomer-facingagentic-workflows

Your mission is to own the last mile of enterprise AI deployment for our own platform Unum. Our Enterprise Superintelligence platform is built to transform how enterprises operate, but getting it to actually run inside complex organizations is what makes it real. As an AI Deployment Engineer, you own the last mile: taking Unum into complex customer environments, connecting it to real systems, shaping workflows with users, and making sure the platform creates measurable adoption and impact.

This is not a traditional software engineering role, and it is not a classic solutions engineering role either. You are a technical owner embedded close to the customer, responsible for turning messy enterprise reality into working software, repeatable patterns, and stronger platform capabilities.

YOUR IMPACT

  • Own the Last Mile: Own the technical outcome of Unum deployments end to end. You will work directly with customers inside real customer environments, understand how work actually happens, and make Unum usable, trusted, and valuable in production.

  • Customer-Embedded Engineering: Build integrations, templates, and deployment logic around actual customer systems, constraints, and users. You will operate where product, engineering, delivery, and customer reality meet.

  • Platform Learning: Translate specific customer pain into reusable product patterns. You will identify what should stay custom, what should become a template, and what should become part of the core Unum platform.

  • Technical Execution: Build high-impact applications, connectors, agentic workflows, and tools that help Unum deliver faster and more reliably. You will work across prototype, implementation, deployment, monitoring, and iteration.

  • Trust & Adoption: Work directly with users and stakeholders to earn trust, clarify success, and drive adoption. You will not just ship features, but make sure they are used, understood, and delivering value.

  • Agentic Workflows: Design how AI agents surface findings, request feedback, trigger approvals, and escalate when they get stuck. You will help define what governed autonomy looks like in real enterprise workflows.

WHY YOU

  • Experience: 3+ years of professional experience in software, product engineering, applied AI, or forward deployed engineering. Experience as a founder, early engineer, technical lead, or customer-facing builder is a strong plus.

  • Technical Depth: Strong engineering fundamentals to build full-stack applications. Proficiency in Python and experience with TypeScript, cloud infrastructure, integrations, and Terraform

  • AI Native: You have built with LLM APIs and understand how to turn model capabilities into useful workflows, not just demos.

  • Customer Proximity: You enjoy working close to users, understanding their real constraints, and turning ambiguous problems into working systems.

  • Product Judgement: You do not just build what is asked. You understand why something matters, how it affects adoption, and when to challenge the request.

  • Execution Orientation: You are comfortable with messy environments, unclear requirements, legacy systems, stakeholder complexity, and production constraints. You make progress without needing a perfect brief.

  • Founder Mindset: You take ownership, create structure where none exists, and care deeply about whether the solution actually works in the field.

WHY UNUM

Less talking, more doing. Join us and push the boundaries of AI.

  • Driving seat: Whether you want to grow further in your role or expand scope and responsibilities at one point, we shape the path together and provide support to accelerate your career in our fast evolving environment.

  • Drive innovation from the center: Help us scale and evolve Unum, the core platform powering ML6’s next-generation AI capabilities.

  • Transparent rewarding: We offer an attractive, optimized total package. Your salary depends on your expertise and impact. This expertise will be translated to a level and scope group on our salary grid and will be defined during the hiring process. Check out our Reward Philosophy to read more.

How we rate this

Forward Deployed Engineer at ML6 rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsApplied AIFull StackCustomer FacingAgentic WorkflowsPython

Also common in forward deployed engineer jobs at this level

Pay

Typical forward deployed engineer job
$180k

This posting doesn't list pay. Use the typical forward deployed engineer figure when pay comes up. See forward deployed engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Tell me about a project where applied ai was part of your work. What did you do?
  3. Tell me about a project where full stack was part of your work. What did you do?
  4. Tell me about a project where customer facing was part of your work. What did you do?
  5. Tell me about a project where agentic workflows was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, Applied AI, Full Stack, Customer Facing, and Agentic Workflows. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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