Staff Software Engineer (Forward Deployed)

Invisible Technologies

San Francisco, New York (CA, NY)

Hybrid

USD 210,000 - 300,000

Full time

14 days+

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Benefits offered by this job

Bonus
Equity

Job summary

Invisible Technologies in San Francisco seeks a Staff Software Engineer (Forward Deployed) to lead end-to-end AI-powered client solutions, shaping architecture, and guiding deployment strategies. You will work closely with clients, drive strategy, and deliver impactful results in a hybrid role with hands-on model work.

You will mentor engineers, design scalable systems, and create reusable components while balancing performance, cost, and reliability in enterprise settings.

Qualifications

  • 8+ years of software engineering experience with data, ML, or backend systems.
  • Strong proficiency in Python and ML/LLM frameworks (e.g., Hugging Face, LangChain, OpenAI, Pinecone).
  • Experience with full-stack/API deployment patterns using Docker, FastAPI, Kubernetes, and cloud environments (AWS/GCP).
  • Data governance and operations experience (e.g., Unity Catalog, policy management, data contracts).
  • Excellent communication and ability to own projects from scoping to deployment in ambiguous environments.

Responsibilities

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

Skills

Python
ML/LLM Frameworks
API Design
Distributed Systems
On-call Readiness
Client-facing Communication
System Design
Messy Data Handling

Education

Bachelor’s degree in Data Science or Computer Science

Tools

Docker
Kubernetes
FastAPI
AWS
GCP
Kafka
Unity Catalog
Delta/ETL pipelines

Job description

Staff 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 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 clients.

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
  • 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
What We Need
  • 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, 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
  • 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
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.

For this position, the annual salary range is: $210,000 – $300,000

Offers will also include bonus + equity.

Additional details on total compensation and benefits will be discussed during the hiring process.

What It's Like to Work at Invisible

At Invisible, we’re not just redefining work—we’re reinventing it. We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale. Ownership is at the core of everything we do. Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world‑class clients pushing the boundaries of AI.

We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity. The pace is fast, the challenges are big, and the growth is unmatched. We’re not for everyone, and we’re OK with that. If you’re looking for predictable routines, this isn’t the place for you. But if you’re driven to create, thrive in dynamic environments, and want a front‑row seat to the AI revolution, you’ll fit right in.

Equal Opportunity Statement

We’re an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law.

Due to a high volume of candidates, Invisible may use automated decision‑maker technologies to filter candidates based on response to our application questions and other provided information. Our use of automated decision‑making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria. If you object to our use of automated decision‑making please contact us.

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