Software Engineer - Forward Deployed

About Invisible

Invisible Technologies is the AI operating system for the enterprise. Our end-to-end AI Software Platform structures messy data, builds digital workflows, deploys agentic solutions, evaluates/measures impact, and mobilizes relevant human experts. Invisible has trained foundation models for more than 80% of the world’s leading AI model providers, including Cohere, Microsoft, and AWS, and we have the expertise to customize AI for any industry, function, or use case.

Invisible makes AI work in the real world. In 2024, we reached $134M in revenue and were named the #2 fastest growing AI company on the Inc. 5000.

As a Staff Forward Deployed Engineer (FDE) at Invisible, you’ll lead high-impact, AI-powered solutions that reshape how our clients operate their most critical workflows. You won’t just build and deploy — you’ll drive the strategy, architecture, and execution of end-to-end systems, working directly with client.

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.

• Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI‑driven solutions
• Identify transformational opportunities in messy, ambiguous workflows and turn them into repeatable systems
• Lead architecture design and trade‑off discussions across performance, scalability, cost, and reliability
• Own projects from first discovery call through full deployment — including client‑facing delivery, internal coordination, and post‑launch iteration
• Build shared infrastructure, reusable components, and internal playbooks to level‑up the team
• Coach and mentor mid‑level engineers and help shape the culture of forward‑deployed AI engineering at Invisible

• 8+ 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, Lang Chain, 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
• Ability to travel roughly 25–50% of the time, sometimes short‑notice trips—primarily across North America with occasional international roll‑outs—to work directly on‑site with clients
• Strong engineering background demonstrated by a Bachelor’s degree in Data Science, Computer Science and related fields OR equivalent professional experience

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.

For this position, the annual salary ranges by location are:

• Tier 1: $215,000 - $310,000
• Tier 2: $195,000 - $280,000

* Offers will also include bonus + equity + benefits

An Invisible Talent Acquisition Partner can provide more information on which locations are included in each of our geographic pay tiers during the interview process. For candidates outside the U.S., compensation will be adjusted to reflect local market conditions and…