Top Tech Jobs & Startup Jobs in NYC, NY

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

Build and deploy AI-powered solutions for clients by scoping ambiguous problems, designing LLM workflows, integrating data and retrieval systems, and creating scalable production tooling. Collaborate with technical and non-technical stakeholders, iterate based on operator feedback, optimize workflows, and support customer deployments. The role requires strong Python and software or ML engineering skills, production deployment experience, communication abilities, customer on-call availability, travel as needed, and hybrid office attendance.

Designs benchmarks, reinforcement learning environments, evaluation methodologies, scoring frameworks, and reproducible evaluation architectures for frontier models. Builds and ships production code, maintains data pipelines, analyzes results, and collaborates with research scientists, solutions architects, and ML engineers. The role combines independent research methodology with hands-on engineering across agentic systems, model evaluation, and RL infrastructure.

Own strategic planning, workflow automation, compliance operations, systems support, data monitoring, documentation, vendor communications, and cross-functional coordination for a Legal and Compliance team. Translate priorities into roadmaps, improve recurring processes, troubleshoot business systems and data issues, and guide application requirements and QA while maintaining accuracy in a high-pressure environment.

Own discovery, scoping, delivery, and stakeholder management for AI-enabled data products serving enterprise financial-services clients. Lead workshops, define success metrics, manage timelines and OKRs, coordinate engineering teams, design automation and human-in-the-loop solutions, and maintain executive relationships. The role also requires data analysis, governance, quality, metadata, lineage, playbook development, mentoring, and collaboration with product and sales teams.

The Enterprise Solutions Manager drives operational excellence and client success through strategic analysis, process optimization, and project management, collaborating with various teams to deliver AI solutions.

Manage relationships with strategic healthcare clients, oversee complex projects, innovate operational processes, and lead large teams to improve AI training and application.

Leads operational delivery for complex enterprise AI engagements, aligning commercial, engineering, and executive client stakeholders. Owns multi-workstream execution, agile delivery ceremonies, requirements scoping, risk mitigation, KPI and ROI analysis, process design, and business cases. Partners with technical leads on strategic deployments, structures ambiguous challenges into scalable frameworks, advises senior clients, and mentors Enterprise Solutions Managers and delivery teams.

Leads enterprise client engagement, solution design, operational process creation, cross-functional project delivery, workflow optimization, team reviews, staff mentoring, performance analysis, and real-time analytics initiatives. The role bridges enterprise clients, global talent, and internal product, engineering, and operations teams while building scalable processes and supporting the launch of a next-generation marketplace.

Work directly with clients to scope, prototype, and deploy AI-powered workflows. Build scalable systems using LLMs, embedding and retrieval systems, and backend infrastructure. Translate messy data and operational constraints into production-ready solutions, iterate with stakeholders, and maintain deployed systems (including on-call support).