Top AI Engineer Jobs in NYC, NY

Lead design, build, and deploy production-scale generative AI and agentic systems: foundation model training, LLM inference, vector search, guardrails, evaluation, observability, and performance optimization across cloud infrastructure.

Lead design and delivery of full‑stack, cloud‑native AI and GenAI solutions; define AI strategies; architect secure, scalable platforms; mentor engineering teams; run pilots, integrate successful technologies, and partner across cloud, security, data, and business stakeholders to improve developer experience and drive enterprise adoption.

Lead development of AI-powered features and scalable agent infrastructure for Hex. Partner with Research on model prompting, build experimentation tooling, and deliver performant full‑stack user experiences using web and backend systems. Mentor engineers and drive major product initiatives.

Lead ML Engineer for Finance Tech to design, build, deploy, and maintain AI/ML systems (including LLMs and RAG). Partner cross-functionally to create production data pipelines, model evaluation, governance, observability, and responsible AI practices while contributing technical vision and scaling AI infrastructure.

Lead design, build, deploy, and support foundational AI systems and products (LLM training/inference, similarity search, guardrails, evaluation, observability). Optimize large-scale AI performance and collaborate with cross-functional teams to produce responsible, scalable AI solutions.

Lead the development of AI software components for Capital One, including model training, inference, and system optimization. Collaborate with cross-functional teams to deliver groundbreaking AI solutions, ensuring quality and scalability while mentoring junior team members.

As a Lead AI Engineer at Capital One, you will design and develop AI systems, collaborate with cross-functional teams, and optimize AI solutions for performance and scalability.

As a Distinguished AI Engineer, you will design and develop AI software, partner with cross-functional teams, and create optimized AI systems to enhance customer interaction and improve banking services.

The role involves partnering with cross-functional teams to design, develop, and deploy AI software solutions, focusing on large language models and AI optimization techniques.

Lead design, development, deployment, and optimization of large-scale AI/ML systems (training, inference, orchestration, observability). Collaborate cross-functionally to build responsible, scalable generative AI and agentic platforms, improve performance and cost, and shape long-term ML systems roadmap.

Lead strategy and hands-on implementation for enterprise developer insights and distributed AI telemetry. Architect streaming, data engineering and ML/AI inference platforms, enforce privacy and risk controls, scale telemetry to billions of events, and mentor engineering leaders to translate AI telemetry into measurable business outcomes.

As a Principal AI/ML Engineer, you will lead the development of machine learning solutions for advertising, focusing on optimization, personalization, and deploying models within a highly scalable infrastructure.

As an AI Product Engineer, you'll build and scale AI-powered features for Notion's Custom Agents, collaborating with teams to enhance user experience and implementing cutting-edge technologies.

As a Staff Applied AI Scientist, you will design and deploy AI systems using LLMs, improve agent performance, and collaborate with engineering to enhance systems for customer impact.

The role involves designing, building, and maintaining an MLOps platform, developing workflows for ML applications, and integrating various technologies while supporting agile teams.

The role involves designing, developing, and optimizing AI software components, collaborating with cross-functional teams, and contributing to the technical vision of AI systems at Capital One.

Lead design, build, deploy, and support scalable, responsible AI systems (foundation model training, LLM inference, similarity search, guardrails, observability). Collaborate with cross-functional teams, optimize model performance and cost, and shape technical vision and roadmap for foundational AI platform services.

Design and ship production LLM features for a SaaS product: build customer intelligence from recordings and text, prioritize testimonials using metadata, create AI-powered surveys/interviews, iterate via research, prototyping, deployment, and evaluation. Own technical decisions and deliver measurable outcomes working closely with engineering leadership and customers.

Embed with strategic enterprise customers to prototype, build, and productionize full-stack generative AI and agentic applications; advise on AI strategy, codify repeatable solution patterns, mentor teams, and channel field feedback to product. Focus on scalable, secure AI architectures and LLM/MLOps practices to operationalize RAG, fine-tuning, semantic search, and agentic workflows.

Lead design, procurement, and lifecycle management of on-prem AI infrastructure. Act as product owner translating data science needs into scalable compute, storage, networking, and accelerator platforms. Drive RFI/RFPs, architect high-performance systems for large-scale training and low-latency inference, define infrastructure standards, partner with MLOps/data science/security/governance, influence executives, and evaluate emerging AI infrastructure technologies.

Design, build, deploy, and maintain high-quality software and AI solutions for investment management. Break down complex problems, write well-tested code, mentor teammates, collaborate cross-functionally, troubleshoot production incidents, and ensure scalable, secure integrations while prioritizing client satisfaction.

Lead design and build of an enterprise AI content platform: RAG-backed knowledge library, embedding search pipeline, prompt MLOps, validation/critic pipelines, shared platform APIs, architecture and mentorship for production LLM systems.

The role involves leading AI product development, working with cross-functional teams to enhance AI systems, and optimizing large-scale production AI systems.

Lead design, develop, deploy, and support large-scale AI systems (foundation model training, LLM inference, vector search, guardrails, observability). Partner cross-functionally to optimize performance, scalability, and cost, and shape long-term foundational AI technical vision and roadmap.

Own and administer Salesforce and NetSuite while designing and deploying production-grade AI-driven automations and agent workflows. Ensure data governance, PHI/HIPAA compliance, release management, and quote-to-cash integrity. Partner cross-functionally to prioritize work, coach teams, document systems, and measure impact of automation on operations and revenue.