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:

About The Role

As a Principal 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.

**Please note - We are always looking to connect with talented individuals for this role. This posting is part of our ongoing effort to build a strong pipeline of candidates and may not correspond to an immediate opening. Candidates who move forward in the process may be considered for current and future opportunities as they arise.

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

• 10+ 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 ranges by location are:

• Tier 1:  $250,000 - $366,000
• Tier 2:  $227,000 - $333,000

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.

You will need to be based in the Greater NYC area and be willing to work from the Manhattan office 3-4 days a week.

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 distributed systems skills — 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
• 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 ranges by location are:

About The Role

We are seeking a highly skilled and driven Principal 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, and 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 or London.

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

• 10+ 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.