Top Tech Jobs & Startup Jobs in NYC, NY

Build and deploy production generative AI and agentic systems for enterprise clients. Responsibilities include identifying high-value problems, shaping architecture, developing multi-agent workflows, APIs, data pipelines, integrations, and distributed systems, and owning deployments through measurable impact. The role requires hands-on ownership of evaluation, observability, security, reliability, scalability, latency, and cost, along with direct collaboration and communication with senior client stakeholders.

Owns enterprise AI engagements from signed SOW through production deployment, adoption, and renewal. Leads client relationships, delivery scope, timelines, staffing, risks, executive communications, P&L, margin, change orders, and expansion opportunities. Manages AI Engagement Leads, Forward Deployed Engineers, and delivery teams while partnering with technical leaders on architecture and production readiness. Requires strong financial-services consulting or delivery experience, technical fluency in AI systems, executive presence, and the ability to work onsite with New York-area clients several days per week.

Lead end-to-end GenAI engagements for Fortune 500 clients: drive client relationships, select use cases, provide technical direction, manage delivery timelines, coordinate cross-functional teams, mitigate risks, and ensure business impact from POC to full-scale implementation.

Own the vision, roadmap, prioritization, and delivery of back-office operations and controls platforms supporting fund accounting and global finance. Partner with controllers, finance, operations, engineering, and technology teams to modernize workflows, reporting, automation, and governance. Translate fund control requirements into product specifications, user stories, and acceptance criteria while managing dependencies, risks, milestones, and stakeholder communication. Identify practical AI opportunities to improve operational efficiency.

Lead end-to-end delivery of software-engineering data programs for frontier AI labs: design and run data pipelines, coordinate 100–1,000+ contributors, ensure annotation and dataset quality, manage client relationships, diagnose bottlenecks, and codify scalable operational playbooks.

Lead discovery with stakeholders to map workflows and controls, write clear problem statements and delivery-ready requirements (user stories, acceptance criteria), partner with product and engineering, support UAT and testing, maintain traceability and auditability, and use AI tools responsibly to accelerate analysis and documentation.

Own Turing’s AI ecosystem partner channel, driving partner-sourced revenue, co-selling, referrals, pipeline, and enterprise account planning. Manage partner programs including onboarding, deal registration, certifications, tiers, funding, training, reporting, business reviews, and executive engagement. Coordinate competing technology partners fairly, ensure delivery commitments are staffed, and collaborate across sales, delivery, and industry teams. Build case studies, grow channel revenue, and potentially develop a partner team.

Conduct research on frontier AI systems and develop datasets, experiments, prototypes, tooling, evaluation frameworks, and reinforcement learning environments. Investigate synthetic and agentic data generation, post-training, model understanding, benchmarks, and evaluation. Collaborate with research, engineering, product, and operations teams to translate findings into scalable AI applications, while contributing to technical publications, open-source work, mentorship, and the broader AI research community.

Conduct original research to develop frontier STEM benchmarks, evaluations, synthetic data methods, hallucination and reliability techniques, and agentic science workflows. Responsibilities include identifying research gaps, designing experiments, building evaluation pipelines, validating results, constructing benchmarks, and publishing findings. The role requires strong knowledge of modern LLMs, scientific judgment, quantitative reasoning, Python, technical writing, and independent research execution. This is an in-office position five days per week in San Francisco, Palo Alto, or Seattle.

Conduct frontier AI research and build research-grade datasets, prototypes, tooling, reinforcement learning environments, benchmarks, and evaluation frameworks. Design rigorous experiments, train and evaluate models, investigate synthetic and agentic data generation, and translate findings into scalable products. Collaborate with research, engineering, product, and operations teams, communicate technical insights, contribute to publications and open-source work, and mentor peers. This is a fully onsite role based in San Francisco, Palo Alto, or Seattle.