Software Engineer (Forward Deployed)

About Invisible 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. 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. 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. 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. About The Role As a 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. 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. What You’ll Do Collaborate with delivery leaders to scope technical solutions to operational problems Identify workflow optimizations through deep engagement with customer problems and work to build into a stable and scalable solution Design and implement AI-powered workflows using LLMs, embedding models, retrieval systems, and automation tools Translate messy real-world constraints (e.g., inconsistent data, latency requirements) into elegant engineering solutions Iterate quickly based on real-time feedback from operators and clients Build reusable tooling and infrastructure that accelerates future deployments What We Need Hands-on experience in software engineering or ML engineering — through professional roles, internships, or coursework/research projects Strong Python skills and familiarity with libraries like PyTorch, Hugging Face, LangChain, or OpenAI APIs Solid understanding of data pipelines, APIs, and production deployment (e.g., Docker, FastAPI, GCP/AWS) Experience building usable systems from messy data and ambiguous requirements Strong communication skills — you can explain technical decisions to delivery teams and client stakeholders Entrepreneurial mindset and comfort working in fast-moving, unstructured environments Be willing to be on-call for our customers when situations arise …