Top Tech Jobs & Startup Jobs in NYC, NY

Lead design, development, deployment, and support of foundation model training and LLM inference platforms. Build similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, and scalability; contribute to technical vision and roadmap while partnering across engineering, research, product, and program teams.

Lead end-to-end design systems for premium digital products: build and govern component libraries and token pipelines, ensure code parity with front-end repos, design AI-native guardrails and data schemas, run QA and UX metrics, mentor designers, and create documentation and enablement to scale system contributions and preserve cohesive customer experiences.

Lead ML engineer responsible for designing, building, deploying, and monitoring production ML systems at scale. Collaborate with product and data science teams, develop ML architectures and data pipelines, apply CI/CD and cloud-based MLOps, retrain and govern models, and ensure performance, reliability, and responsible/explainable AI practices.

As a Senior Lead AI Engineer, you'll design and support AI systems, collaborating with teams to enhance customer interactions and deliver AI-powered products.

Lead Counsel for Capital One Shopping, overseeing legal support for business operations, providing legal advice across various teams, and managing a team of attorneys.

Lead technical risk advisory for SRE and cloud-native engineering, assess resiliency, SLIs/SLOs, CI/CD, and observability, perform independent risk reviews, drive AI/automation adoption, and deliver executive-facing risk reporting and remediation guidance.

Serve as a second-line data risk advisor by validating enterprise analytical tools, conducting risk and gap assessments, influencing stakeholders, designing controls, leading validation projects, mentoring staff, and ensuring data management practices meet regulatory and enterprise risk standards.

Lead development of next-generation entity resolution solutions using transformers, graph ML, deep learning, and big-data tooling. Partner with engineers and product to design, train, evaluate, validate, and deploy ML models at scale; leverage Agentic AI workflows; translate technical work into business impact across enterprise use cases.

Lead and grow an AI engineering team to design, build, deploy, and support production-scale generative AI systems. Oversee foundation model training, LLM inference, vector search, guardrails, evaluation, governance, and observability. Make build-vs-buy decisions across open source and SaaS, optimize LLM performance for cost/latency/throughput, set technical vision and roadmap, and attract/mentor top AI engineering talent.

Lead development of next-generation entity resolution using transformers, graph ML, and deep learning at scale. Partner with engineers and product to design, train, validate, and deploy models on AWS/Spark, leverage agentic AI workflows, and translate technical work into business impact across enterprise use cases.