Senior Backend Engineer

Job Summary

Pyyne is seeking a Sr. Backend Engineer with experience in Python and LLM-based systems to work as a consultant out of our New York Office. This is a high-impact role for Pyyne as we build up our Applied AI services and continue to create real business value for our clients.

A successful candidate in this role will build the backend of an AI-powered solution for a private equity client. They have a strong mental model of the Generative AI space: they can speak to the technical differences between models and frameworks, design multi-step agent workflows, and decide when and how to use LLM capabilities beyond a coding assistant. This role is highly client-facing and suits an engineer who is credible and confident with non-technical stakeholders.

This is a hybrid role, with three days per week in the office. It carries long-term growth potential for technical leadership across the company.

Key Responsibilities

• Build and extend the Python backend of an AI-powered solution for a private equity client
• Integrate LLMs and agentic workflows into backend services, including multi-step agent design
• Build and optimize data ingestion pipelines that bring external data sources into the application layer
• Collaborate closely with a small cross-functional team (frontend, DevOps, full-stack) to ship features end-to-end
• Meet production standards for reliability, performance, and data integrity
• Translate business needs from non-technical stakeholders into technical designs, and explain tradeoffs clearly
• Present your work with confidence and earn the client's trust through clear, credible communication
• Take ownership of backend delivery with minimal oversight and contribute to architectural decisions

Must Have Skills

• 3+ years of strong Python backend engineering (FastAPI, SQL), with hands-on work in AI systems
• Production experience building with LLMs and agentic systems, including multi-step agent workflows
• Strong mental model of the Generative AI space: can compare models and frameworks and decide when and how to use LLMs
• Stakeholder management with technical teams and non-technical business leaders, ideally in a client-facing or consulting role
• Experience working in structured, production environments

Nice to Have Skills

• Data engineering exposure, such as ingestion pipelines or data warehousing, even if not a primary specialty
• Finance, private equity, or consulting background
• Experience at an AI-focused company or a large technology company
• Experience owning a roadmap and prioritizing competing initiatives by feasibility, ROI, and readiness
• Interest in growing into a technical lead role

Benefits

• Hybrid working environment (3 days per week in office, New York).
• Career development opportunities in a fast-growing company.
• 401(k) with match
• Comprehensive Healthcare Plan with Vision and Dental included