Senior Software Engineer (Forward Deployed) at Invisible Technologies in New York, NY
- Company: Invisible Technologies
- Location: London | New York | San Francisco
- Salary: $110K – $162K
- Job type: full time
- Workplace: hybrid
- Posted: 2026-10-11
All open roles at Invisible Technologies
Job description
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 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. 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 6+ years of software engineering experience, including significant time spent building data, ML, or backend systems Python & ML/LLM Frameworks: Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems Deployment & Infrastructure: Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS) Platform Orchestration: Experienced with workflow orchestration libraries, pub/sub systems (Kafka), and schema governance Data Management: 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 Strong product and system design instincts — you understand business needs and how to translate them into technical architecture Experience building usable systems from messy data and ambiguous requirements Excellent communication and client-facing skills; you’ve led conversations with technical and non-technical stakeholders alike Proven experience owning projects from scoping through deployment in ambiguous, high-stakes 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 What’s In It For You 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. The annual salary range for this position, depending on level, is: £110,000 - £162,000 GBP Bonus and equity is included in all full-time, non commission 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, eve
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