at Invisible · 251-500 employees
Invisible Technologies provides an enterprise AI software platform that structures data and builds agent-driven workflows by combining modular infrastructure with human expertise.
<div class="content-intro"><h2><strong>About Invisible</strong></h2> <p>Invisible Technologies makes AI work. Our end-to-end AI platform structures messy data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise where it matters most.</p> <p>Our platform cleans, labels, and structures company data so it is ready for AI. It adapts models to each business and adds human expertise when needed, the same approach we have used to improve models for more than 80% of the world’s top AI companies, including Microsoft, AWS, and Cohere.</p> <p>Our successes span industries, from supply chain automation for Swiss Gear to AI-enabled naval simulations with SAIC, and validating NBA draft picks for the Charlotte Hornets.</p> <p>Profitable for more than half a decade, Invisible reached $134M in revenue and ranked as the number two fastest growing AI company on the 2024 Inc. 5000. In September 2025, we raised $100M in growth capital to accelerate our mission of making AI actually work in the enterprise and to advance our platform technology.</p></div><h2><strong>About The Role</strong></h2> <p>As a Senior Software Engineer, Forward Deployed Engineer (FDE) you'll work directly with clients and our internal delivery teams to build and deploy AI-powered solutions that transform how work gets done. You’ll own projects end-to-end: scoping ambiguous problems, prototyping AI workflows, and deploying scalable systems on top of our products — all while interfacing with technical and non-technical stakeholders.<br><br>This is a hybrid role: equal parts AI engineer, software builder, and technical consultant. It's perfect for someone who wants to be hands-on with models and close to the impact they generate.</p> <h4><br><em>**Please note - We are always looking to connect with talented individuals for this role. This posting is part of our ongoing effort to build a strong pipeline of candidates and may not correspond to an immediate opening. Candidates who move forward in the process may be considered for current and future opportunities as they arise.</em><br><br></h4> <h2><strong>What You’ll Do</strong></h2> <ul> <li>Collaborate with delivery leaders to scope technical solutions to operational problems</li> <li>Identify workflow optimizations through deep engagement with customer problems and work to build into a stable and scalable solution</li> <li>Design and implement AI-powered workflows using LLMs, embedding models, retrieval systems, and automation tools</li> <li>Translate messy real-world constraints (e.g., inconsistent data, latency requirements) into elegant engineering solutions</li> <li>Iterate quickly based on real-time feedback from operators and clients</li> <li>Build reusable tooling and infrastructure that accelerates future deployments</li> </ul> <h2><strong>What We Need</strong></h2> <ul> <li>6+ years of software engineering experience, including significant time spent building data, ML, or backend systems</li> <li><strong>Python & ML/LLM Frameworks:</strong> Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems</li> <li><strong>Deployment & Infrastructure:</strong> Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS)</li> <li><strong>Platform Orchestration: </strong>Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance</li> <li><strong>Data Management:</strong> Expertise in data governance and operations, including Unity Catalog and policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, and replay processes</li> <li>Strong product and system design instincts — you understand business needs and how to translate them into technical architecture</li> <li>Experience building usable systems from messy data and ambiguous requirements</li> <li>Excellent communication and client-facing skills; you’ve led conversations with technical and non-technical stakeholders alike</li> <li>Proven experience owning projects from scoping through deployment in ambiguous, high-stakes environments</li> <li>Be willing to be on-call for our customers when situations arise</li> <li>Able to travel 25–50% of the time as needed for on-site client engagements</li> <li>Strong engineering background demonstrated by a Bachelor’s degree in Data Science, Computer Science and related fields OR equivalent professional experience</li> </ul> <h2><strong>What’s In It For You</strong></h2> <p>Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity.<br><br>For this position, the annual salary range by location:</p> <ul> <li><strong>NY / SF: </strong>$180,000 - $264,000 USD</li> <li><strong>London: </strong>£110,000 - £162,000 GBP</li> </ul><div class="content-conclusion"><p>*Offers will also include bonus + equity</p> <p>You can find more information about our geographic pay tiers <strong><a class="c-link" href="https://invisibletech.ai/compensation-and-pay-tiers" target="_blank" data-stringify-link="https://invisibletech.ai/compensation-and-pay-tiers" data-sk="tooltip_parent">here</a>.</strong> During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living.<br><br>Bonuses and equity are included in all offers. Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions. Because of this, every offer is unique. Additional details on total