Staff Software Engineer (Forward Deployed)

Invisible Technologies Inc.; New York, San Francisco (NY, CA); Hybrid; USD 210,000 - 300,000; Full time

Job summary

Invisible Technologies Inc. is seeking a Staff Forward Deployed Engineer to lead AI-powered client solutions, shaping architecture and strategy across complex workflows. You’ll own end-to-end delivery from discovery through production, blending hands-on model work with technical consulting for enterprise customers.

The role blends AI engineering with system design, MLOps practices, and cross-functional collaboration, with travel to on-site engagements and a hybrid NYC-area setup.

Qualifications

• 8+ years of software engineering experience, including data, ML, or backend systems.
• Deep proficiency in Python with hands-on experience using Hugging Face, LangChain, OpenAI, Pinecone, and related ecosystems, including LLMs and AI Agents
• Deployment & Infrastructure: Full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS, Azure)
• Platform Orchestration: Workflow orchestration libraries, pub/sub systems (Kafka), and schema governance
• Data Management: Data governance and Unity Catalog, policy management, cluster/job orchestration, data contracts and quality enforcement, Delta/ETL pipelines, replay processes
• ML Operations (for teams with an applied AI/ML focus): MLOps frameworks, model versioning, monitoring, lifecycle management, and scalable ML systems like RAG pipelines
• Strong product and system design instincts; translate business needs into architecture
• Experience building usable systems from messy data and ambiguous requirements
• Excellent communication and client-facing skills; led conversations with technical and non-technical stakeholders
• Proven experience owning projects from scoping through deployment in ambiguous environments
• Willingness to be on-call for customers
• Travel: Willingness to travel for on-site client engagements as needed
• Onsite: NYC-based teams require 3 days onsite; local requirements vary

Responsibilities

• Scope, design, and lead AI-driven solutions with clients, including LLM and agentic systems
• Identify transformational opportunities in messy workflows and create repeatable systems
• Lead architecture design and trade-offs for performance, scalability, cost, reliability (RAG pipelines)
• Own projects from discovery through full deployment and post-launch iterations
• Build shared infrastructure, reusable components, and internal playbooks (MLOps practices)
• Coach and mentor mid-level engineers and shape forward-deployed AI culture at Invisible

Skills

Python

ML/LLM Frameworks

Hugging Face

LangChain

OpenAI

Pinecone

LLMs

AI Agents

Docker

FastAPI

Kubernetes

Cloud (GCP/AWS/Azure)

Tools

Docker

FastAPI

Kubernetes

Job description

Staff Software Engineer (Forward Deployed)

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 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. The team is increasingly focused on applied AI work — building and deploying LLM-powered and agentic systems in production — so strong ML engineering instincts can be a valuable addition alongside your architecture and leadership experience.

What You’ll Do

• Partner with delivery and executive stakeholders to scope, design, and lead implementation of AI-driven solutions, including LLM and agentic systems
• 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 — including for ML/AI-specific systems like RAG pipelines and production-grade AI applications
• 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, including MLOps practices for model versioning, monitoring, and lifecycle management
• 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, including LLMs and AI Agents
• Deployment & Infrastructure: Skilled in full-stack and API-based deployment patterns, including Docker, FastAPI, Kubernetes, and cloud environments (GCP, AWS, Azure)
• 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
• ML Operations (for teams with an applied AI/ML focus): Experience with MLOps frameworks and best practices — model versioning, monitoring, and lifecycle management — and designing scalable ML systems such as RAG pipelines
• 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 — some NYC-based teams require 3 days per week onsite; your specific requirement will depend on the team you're placed with

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:$210,000 - $300,000 USD

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, every offer is unique. Additional details on total compensation and benefits will be discussed during the hiring process.

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.

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