Forward Deployed Engineer

About Us We are a fast-growing AI platform company expanding into the US market. Our proprietary AI platform, combined with forward-deployed delivery pods and a growing library of practical playbooks, enables mid-market enterprises to become truly AI-native—not through pilots or proof-of-concept projects, but through production AI that transforms how organizations operate. We believe the future of enterprise is AI-native: where intelligent systems and people work together to achieve what was never before possible. Backed by partnerships with leading hyperscalers and frontier AI providers, and already delivering at scale for customers across multiple industries in our home market, we're now bringing that model to the United States. Our ambition is to become the defining AI platform company for the mid-market enterprise globally. The Role You'll work within cross-functional delivery pods alongside AI Transformation Strategists and other Forward Deployed Engineers to take solution designs from concept to production. This is a highly hands-on, client-embedded engineering role. You'll work directly with business users, building and deploying agentic AI solutions that fundamentally improve how they operate. You won't just design solutions—you'll build them. We're not looking for someone who has simply "led AI transformation." We're looking for a curious, high-agency engineer who loves building production systems, moves quickly without sacrificing quality, and genuinely cares about delivering customer outcomes. What You'll Do Agentic Solution Delivery Build, configure, test, and deploy agentic AI solutions within delivery pods. Own implementation from solution design through production. Develop integrations, connection templates, data pipelines, and AI workflows. Hands-On Engineering Build production-ready AI capabilities ("monotiles") that deliver measurable customer value within 60-90 days. Work directly in client environments and on our platform. Client Engagement Embed with client teams (including on-site when appropriate). Understand business workflows, systems, and operational constraints. Translate solution architecture into production-grade technical implementations. Integrations & Data Pipelines Develop API integrations. Build data pipelines and workflow automations. Connect our platform seamlessly into enterprise environments. Production Excellence Deliver reliable, production-grade solutions. Contribute to testing, monitoring, incident response, continuous improvement, and post-launch optimization. Ensure solutions achieve agreed commercial outcomes. Delivery Pod Operations Help shape how delivery pods operate. Improve workflows, collaboration, and scalable delivery practices. AI-Native Operations Help build internal AI-first ways of working. Experiment with new AI tools. Create repeatable playbooks and best practices. Playbook Development Document implementation approaches. Standardize deployment processes. Build reusable delivery methodologies that improve over time. Team Growth Support hiring and mentoring engineers. Raise engineering standards. Help build a culture centered around ownership, speed, and craftsmanship. What You'll Bring Full-stack or platform engineering experience with strong exposure to AI/ML, data engineering, or enterprise SaaS platforms. Strong programming skills in Python and/or TypeScript/JavaScript . Experience writing clean, tested, production-quality code. Understanding of modern AI architectures, including: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Vector databases Embedding pipelines Agentic frameworks Prompt engineering Experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with containers, serverless architectures, CI/CD, and Infrastructure as Code. Experience designing APIs, integrations, and scalable systems. Experience managing enterprise implementations involving multiple stakeholders. Strong project management skills with the ability to manage timelines, dependencies, and competing priorities. Excellent client-facing communication skills and the ability to explain technical concepts to senior stakeholders. A strong bias toward execution—you'd rather build, learn, and iterate than spend weeks writing documentation no one reads. Attention to detail with a passion for documentation and repeatable processes. Genuine curiosity about how AI transforms businesses—not just technically, but operationally. Bonus Points Experience building multi-agent AI systems. Experience with tool orchestration and AI platform development. Experience using AI-assisted development workflows and agentic coding pipelines. Background in technical consulting, solutions delivery, or customer-facing engineering. Experience working at startups or early-stage companies where ambiguity is part of the job. Contributions to open-source AI/ML projects. Experience with Node.js, TypeScript, MongoDB, or PostgreSQL. Show more Show less