Staff Software Engineer, Applied AI (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

We are seeking a highly skilled and driven Software Engineer with a strong background in full-stack development, particularly in backend technologies and Agentic AI, to join our AI/ML team. In this role, you’ll work at the intersection of engineering, data science, and real-world impact, partnering directly with clients and internal stakeholders to design and deploy ML-powered tools that solve meaningful problems.

This role combines hands-on model development with robust backend engineering and infrastructure work. You’ll help build scalable systems, support R&D initiatives, and ensure rapid iteration and deployment of machine learning solutions in dynamic, production-ready environments. You will work embedded with our top clients and the client teams to conduct use case discovery with senior stakeholders directly, developing solutions that address complex client needs. This will require being onsite with clients 3-4 days a week on a regular basis in New York.

What You’ll Do

• As part of the Forward Deployed Engineering team, you’ll contribute during a phase of rapid growth as we focus on scaling models and improving platform performance. You’ll help build backend systems, support client-facing deployments, and enable smoother workflows for machine learning solutions.


• Develop and Maintain AI/ML Systems: Build robust, scalable backend systems that support machine learning operations and data processing pipelines.


• Cloud Operations and Management: Oversee and optimize cloud infrastructure to ensure efficient deployment and operation of ML models.


• Problem Solving: Independently explore and address complex problem spaces to improve system capabilities and performance without extensive guidance.


• Cross-Functional Collaboration: Work closely with ML engineers and data scientists to integrate advanced ML technologies, ensuring seamless operations across various platforms.


• Client Engagement: Collaborate directly with Invisible’s clients, working embedded with client teams to support use case discovery, product development, and AI deployment.


• Innovation and R&D: Actively participate in research and development of new tools that can enhance our AI capabilities and workflows.

What We Need

• 8+ years of software engineering experience, with a strong focus on ML engineering and deploying machine learning models in production.


• Extensive experience in full-stack development, particularly in backend environments that support AI/ML workloads.


• Prior experience working directly with clients in use case discovery, product development, and leading client engagements.


• Technical Expertise: Strong proficiency in Python, with deep expertise in LLMs, AI Agents, and ML model development.


• Experience designing and deploying scalable ML systems, such as retrieval-augmented generation (RAG) pipelines and production-grade AI applications.


• Extensive experience with cloud platforms (AWS, GCP, Azure) and operational best practices for ML workloads.


• Familiarity with Kubernetes and other container management tools.


• Ability to write well-structured, organized code and automated unit/E2E tests.


• Comfortable with polyglot persistence models (SQL vs. NoSQL).


• ML Operations: Experience with MLOps frameworks and best practices; familiarity with DevOps principles as applied to machine learning models, including model versioning, monitoring, and lifecycle management.


• Problem Solving: Ability to operate independently in unstructured environments, demonstrating a proactive and investigative approach to tackling challenges.


• Communication: Excellent communication skills, with the ability to collaborate effectively in dynamic, cross-functional teams, including data scientists, researchers, and software engineers.

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 ranges by location are:

Salary Range

$209,000 - $307,000 USD

You can find more information about our geographic pay tiers here . During the interview process, your Invisible Talent Acquisition Partner will confirm which tier applies to your location. For candidates outside the U.S., compensation is adjusted to reflect local market conditions and cost of living.

Bonuses and equity are included in offers above entry level. 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, every offer is unique. 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 okay 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.

Country Hiring Guidelines:
Invisible is a hybrid organization with offices and team members located around the world. While some roles may offer remote flexibility, most positions involve in-office collaboration and are tied to specific locations. Any location-based requirements or hybrid expectations will be communicated by our Talent Acquisition team during the recruiting process.

AI Interviewing Guidelines:
Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey.

Accessibility Statement:

We are committed to providing reasonable accommodations for individuals with disabilities. If you require an accommodation to participate in the application or interview process, please submit your request using our accommodation request form. A member of our team will follow up to support your request.

Here is the link the google form:

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.