Generative AI Engineer

Sourced from snaprecruit.com

A senior hands-on AI engineer role at Atlantic Partners Corporation in New York, serving as the primary technical partner to the Lead AI Engineer. The position owns solution design and implementation for generative AI, retrieval, and agentic workflow initiatives, moving AI products reliably into production. The engineer partners with Data, Platform Engineering, Cybersecurity, and product teams to deliver secure, scalable AI solutions.

• Partner with the Lead AI Engineer to develop reference architectures, engineering patterns, and standards for generative AI, ML, retrieval, and agentic workflows
• Own technical design and implementation for assigned AI products, including model selection, orchestration, retrieval, tools, memory, APIs, and integrations
• Build and apply evaluation frameworks for quality, groundedness, safety, latency, reliability, and cost, including regression testing and release checks
• Implement security and governance controls for identity, access, data handling, privacy, secrets, logging, auditability, and human oversight
• Partner with Data and Platform Engineering on reusable services, deployment, CI/CD, MLOps/LLMOps, observability, scaling, and production operations
• Evaluate models, platforms, and vendors; prototype solutions and inform build-versus-buy decisions
• Mentor AI engineers and provide technical guidance through design reviews and shared learning

• Bachelor's or advanced degree in Computer Science, Engineering, Machine Learning, or related field, or equivalent experience
• 6–10+ years of software, data, ML, or AI engineering experience, including technical design and delivery of production systems
• Strong hands-on experience with LLM APIs and models, RAG, embeddings, vector search, agents, orchestration, evaluation, and AI application security
• Hands-on experience building and running agentic systems in production, including agent harnesses and SDKs (Claude Agent SDK, OpenAI Agents SDK, LangChain, or equivalent)
• Experience designing and deploying Model Context Protocol (MCP) servers and tools
• Experience designing human-in-the-loop workflows with approval gates and asynchronous job orchestration
• Experience building evaluation and regression harnesses for agent outputs
• Strong Python and software-engineering skills, including APIs, distributed systems, cloud services, testing, CI/CD, observability, and secure development
• Experience integrating AI with enterprise data platforms, identity systems, document stores, workflows, and business applications

• Experience with Snowflake, Azure or AWS, modern data stacks, containers, infrastructure as code, and enterprise AI platforms
• Experience in financial services, real estate, private equity, asset management, or another regulated environment