Software Engineer (Forward Deployed)

About the role

About Invisible

Invisible is an Applied AI research company closing the gap between frontier models and the enterprise. We provide the platform infrastructure that makes AI work in production at scale: unify fragmented data, map complex processes, orchestrate and evaluate agents, and stand up hyper-personalized workflow applications fast for companies like Grubhub, Alliance Global, and Thomson Reuters. Where models fall short, we build RL environments and data to fix them. The result: a virtuous cycle between enterprise deployment and model training.

Recognized as Best Predictive Analytics Platform of the Year at the 2026 AI Breakthrough Awards, Invisible makes AI work.

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

- Travel: Willingness to travel for on-site client engagements as needed

- Onsite: Available to work from the office a few days per week, depending on team needs