Principal Backend Engineer (Forward Deployed)

Location: Hybrid in New York or the San Francisco Bay Area; office attendance is required a few days per week, with some New York teams requiring three days onsite. Travel for onsite client engagements is required as needed.

Salary: $250,000–$300,000 USD annual base salary, depending on level and location. Full-time offers also include bonuses and equity.

Company

AI platform company that structures data, automates digital workflows, deploys agentic solutions, measures outcomes, and integrates human expertise for enterprise customers.

What you will do

• Scope, design, and lead implementation of AI-driven solutions, including LLM and agentic systems, with delivery and executive stakeholders.
• Transform messy and ambiguous workflows into repeatable production systems.
• Lead architecture and trade-off decisions covering performance, scalability, cost, and reliability for AI applications and RAG pipelines.
• Own projects from discovery through deployment, including client-facing delivery, internal coordination, and post-launch iteration.
• Build shared infrastructure, reusable components, internal playbooks, and MLOps practices for model versioning, monitoring, and lifecycle management.
• Coach mid-level engineers and help shape forward-deployed AI engineering practices.

Requirements

• 10+ years of software engineering experience, including substantial work with data, ML, or backend systems.
• Deep Python expertise and hands-on experience with Hugging Face, LangChain, OpenAI, Pinecone, LLMs, and AI agents.
• Experience with Docker, FastAPI, Kubernetes, cloud environments, full-stack and API-based deployment patterns.
• Knowledge of workflow orchestration, Kafka, schema governance, data contracts, quality enforcement, Delta/ETL pipelines, and replay processes.
• Strong system design, product thinking, communication, and client-facing delivery skills, with experience owning projects from scoping through deployment.
• Availability for hybrid office work in New York or the San Francisco Bay Area, customer on-call responsibilities, and travel for onsite client engagements.

Nice to have

• Strong ML engineering instincts and experience designing scalable ML systems such as RAG pipelines.
• Experience with Unity Catalog, policy management, cluster and job orchestration, and applied AI/ML systems.
• Bachelor’s degree in Data Science, Computer Science, or a related field.

Culture & Benefits

• Ownership-driven environment focused on advanced AI and human ingenuity.
• Work with enterprise clients on high-impact, ambiguous AI challenges.
• Full-time offers include bonuses and equity.
• Compensation is adjusted by geographic pay tier, experience, skills, internal equity, and market conditions.
• Reasonable accommodations are available throughout the application and interview process.