Job Opportunities API

The engine only matters once it runs Since 2018, Enjins has been building high-performance engines: production-grade ML systems, data infrastructure, and agentic AI, engineered by our AI Engineers from architecture to implementation. Real systems that ship, not slideware. But an engine doesn't move anything on its own. It has to go into a vehicle, and every client's vehicle looks different: a CRM stitched together from three different tools in the rush to scale, sensor data still sitting in someone's personal spreadsheet, no dedicated security team yet so every integration gets extra scrutiny, an ops process that only lives in one person's head because nobody's had time to document it. That's where you come in. As a Forward Deployed AI Engineer , you take the engine inside the client's actual environment. Not a demo. Production, with their data, their constraints, their people. Forward Deployed & AI Engineering Together, they bridge the gap between cutting-edge technology and real-world business value, working hand-in-hand to build and scale the future of enterprise AI. Forward Deployed AI Engineer: Sits across the table from CEOs, CTOs, and CPOs to uncover what the business actually needs, then translates that into working AI solutions. Combines strong technical implementation skills with a consulting mindset, rapidly building and iterating agentic AI applications that deliver measurable business value. AI Engineer: Designs and builds advanced AI systems, combining deep expertise in LLMs, MLOps, data engineering, and software architecture to solve complex technical challenges. Thrives on architecting scalable solutions and pushing the boundaries of what's technically possible. Interested? See our Senior AI Engineer vacancy Together, they form the engine: one embedded with the client to shape the solution, and the other architecting the robust systems to power it at scale. The role Translate specs into systems. You thrive on ambiguity, taking what clients communicate, and uncovering what they leave unsaid to determine the next architectural choice, integration path, or technical resolution. Construct tailor-made layers. Build and launch client-specific workflows and agents on top of our core Multi-Agent Systems, turning generic code into high-value operational assets for their business. Lead client relationships. Be the go-to senior technical contact from day one, building direct trust with the client without needing to escalate. Make the most of agentic AI. Continuously track new AI developments and apply them to the workflows you build and the impact we can have. Perfect the feedback loop. Share real-world deployment insights with the AI Engineers to shape scalable platform features. Act as a mentor to peers on-site, continuously refining our deployment standards. Serve exciting ventures. Energy & climate scale-ups and VC/PE investors going AI-native. What you'll learn How to turn messy, ambiguous client problems into production-grade AI systems. A skill few engineers get to practice at this scale. Direct, regular exposure to how CEOs, CTOs, and CPOs make technology decisions, and how to earn their trust as a technical authority. Also while joining one of our many Climate x AI events, round tables, podcasts etc. Through AI-Leap, you sharpen your consulting, stakeholder management, and architecture skills alongside your technical growth. Requirements 3+ years of production experience shipping ML/AI systems, not just prototypes, but things that ran with real data and real users. A builder's instinct for messy environments. You don't wait for a clean spec; you go find out what's actually happening in the client's systems. Comfortable working with legacy systems not built with AI in mind, and confident navigating security and compliance requirements. Strong communication across technical and business lines, you can sit with a client's engineers and their