Staff Software Engineer, Applied AI (Forward Deployed)

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.

Responsibilities

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.

Requirements

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.; 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).; Experience with MLOps frameworks and best practices; familiarity with DevOps principles as applied to machine learning models, including model versioning, monitoring, and lifecycle management.; Ability to operate independently in unstructured environments, demonstrating a proactive and investigative approach to tackling challenges.; Excellent communication skills, with the ability to collaborate effectively in dynamic, cross-functional teams, including data scientists, researchers, and software engineers.

Benefits

bonus; equity