# Staff Software Engineer, Applied AI (Forward Deployed)

**Company:** [Invisible Tech](https://hotfix.jobs/companies/invisible-tech)
**Location:** New York, NY
**Role:** ML Engineering
**Salary:** $209k – $307k/yr
**Experience:** 8+ years
**Skills:** Python, LLMs, AI Agents, RAG, MLOps, Kubernetes, AWS, GCP, Azure, DevOps
**Posted:** 2026-03-27

> Builds scalable backend systems and deploys ML models in production for client engagements, working embedded with top clients 3-4 days/week in New York. Requires 8+ years experience in ML engineering, Python, LLMs, cloud platforms, and client-facing work.

## Job Description

## What You’ll Do

- 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.

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