Senior AI Engineer

Senior AI Engineer We're partnering with an innovative AI-driven company building next-generation intelligent systems that automate complex workflows, reasoning tasks, and decision-making processes. We're looking for a hands-on Senior AI Engineer who has experience building and deploying AI products in production, ideally within high-growth startups (Seed, Series A, Series B, or Series C environments). This is an opportunity to help shape core AI architecture, own systems end-to-end, and develop agentic AI capabilities that directly impact the business. This role is hybrid, requiring 3 days per week onsite in New York City. What You'll Do Build Production Agentic AI Systems Design, develop, and deploy production-grade AI applications powered by LLMs and autonomous agent architectures Build multi-agent systems capable of planning, reasoning, memory management, tool usage, and workflow orchestration Develop AI products that move beyond prototypes and operate reliably in real-world production environments Design scalable architectures for long-running agent workflows and complex task execution Own AI Systems End-to-End Lead the full lifecycle from concept and architecture through deployment, monitoring, and continuous improvement Build APIs, services, data pipelines, agent frameworks, and supporting infrastructure Partner closely with Product, Engineering, Design, and Leadership teams to identify high-impact AI opportunities Drive technical decisions around model selection, orchestration frameworks, architecture, and deployment strategies Retrieval, Knowledge & Memory Systems Design and implement advanced RAG architectures Build long-term memory and context-management systems for AI agents Develop integrations with vector databases, knowledge stores, and enterprise data sources Improve retrieval quality, agent accuracy, and reasoning performance across workflows Reliability, Evaluation & Scale Build evaluation frameworks and testing pipelines for AI systems Establish observability, monitoring, guardrails, and governance for production AI applications Improve latency, reliability, scalability, and cost efficiency across AI workloads Create processes that allow AI systems to operate safely and effectively at scale What We're Looking For Required 6+ years of software engineering, machine learning, or AI engineering experience Strong Python engineering background with experience building production systems Demonstrated experience deploying LLM-powered products used by real customers Hands-on experience building multi-agent or agentic AI systems in production Experience with frameworks such as LangGraph, LangChain, CrewAI, AutoGen, OpenAI Agents SDK, or similar Strong understanding of RAG architectures, retrieval systems, vector databases, and embeddings Experience designing distributed systems, APIs, and scalable backend services Experience deploying applications on AWS Strong systems-thinking mindset and ability to operate in fast-moving startup environments Highly Preferred Experience working at venture-backed startups (Seed, Series A, Series B, or Series C) Experience being one of the first AI hires or an early engineering team member Proven track record taking AI products from 0→1 and scaling them in production Experience building AI infrastructure, orchestration platforms, or developer tooling Experience with agent memory, planning, tool calling, MCP, and workflow orchestration Experience deploying production systems using Docker, Kubernetes, Terraform, or modern DevOps tooling Experience evaluating and benchmarking LLMs and autonomous agents Show more Show less