250K–300K USD / year
Principal Backend Engineer (Forward Deployed)
AIHybrid — New York, San Francisco Bay Area
Published on 2026-11-06
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About this role
Lead end-to-end development and deployment of AI-powered systems for enterprise clients, from workflow discovery and architecture through launch and iteration. The role combines hands-on engineering, technical consulting, and leadership, with a focus on production LLM and agentic applications.
About the company
Invisible is a technology company that specializes in automating business processes and providing operational support through advanced AI and workforce solutions. They serve enterprises by helping streamline workflows and improve efficiency across various functions.
Stack
PythonHugging FaceLangChainOpenAIPineconeDockerFastAPIKubernetes
What you'll do
- Scope and lead implementation of AI-driven client solutions, including LLM and agentic systems
- Identify opportunities in ambiguous workflows and turn them into repeatable systems
- Lead architecture and trade-off decisions for performance, scale, cost, and reliability
- Own projects from discovery through deployment and post-launch iteration
- Build reusable infrastructure, components, playbooks, and MLOps practices
- Mentor engineers and help shape forward-deployed AI engineering practices
What we're looking for
- 10+ years of software engineering experience, including data, ML, or backend systems
- Deep Python proficiency and hands-on experience with LLM and AI-agent frameworks
- Experience deploying APIs and applications with Docker, FastAPI, Kubernetes, and cloud platforms
- Experience with workflow orchestration, Kafka or other pub/sub systems, and schema governance
- Knowledge of data governance, data quality, ETL pipelines, and replay processes
- Strong system design and ability to translate business needs into technical architecture
- Excellent client-facing communication and experience owning ambiguous projects through deployment
- Willingness to be on call and travel for client engagements; able to work onsite a few days per week
Nice to have
- MLOps experience with model versioning, monitoring, and lifecycle management
- Experience designing scalable RAG pipelines and production ML systems
Benefits
- Bonus and equity included in full-time, non-commission offers