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Your mission is to own the last mile of enterprise AI deployment for our 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.
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.
Experience: 2+ 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.
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.
