Top Tech Jobs & Startup Jobs in NYC, NY

Owns infrastructure, deployment, reliability, and observability for multi-cloud AI systems and autonomous agents. Responsibilities include Terraform-based infrastructure across AWS, Azure, and GCP; managed Kubernetes; incident response; SLOs; on-call operations; compliance automation for HIPAA and SOC 2; customer environment provisioning; and developer deployment platforms. The role also operates observability tooling and supports production AI, inference, and research-to-production workflows.

The Research Engineer/Scientist will advance decision-making in critical industries using optimization and machine learning, collaborating with product managers and engineers.

As a Research Engineer/Scientist in Reinforcement Learning, you will develop RL methods, maintain experimental infrastructure, and collaborate to enhance AI solutions in critical sectors.

As a Research Engineer/Scientist, advance large-scale language model technologies focusing on pre-training, post-training, and Reinforcement Learning, while collaborating with product managers and engineers to implement impactful AI solutions.

Build and operate Percepta’s foundational People Operations infrastructure, including HRIS administration, employee lifecycle workflows, onboarding, offboarding, payroll, benefits, compliance, reporting, documentation, and cross-functional integrations. Serve as the first point of contact for employee questions while partnering with the Head of People to create scalable, accurate, and people-centered processes in a growing NYC-based company.

Lead full-cycle technical recruiting from sourcing through closing. Build candidate pipelines, develop innovative sourcing and recruiting programs, partner with hiring managers and candidates, analyze recruiting data, improve processes, support university and early-talent initiatives, and deliver an exceptional candidate experience in a high-growth AI company.

Lead and develop a team of Applied AI Engineers while remaining hands-on in production code. Own technical outcomes, architecture decisions, engineering standards, customer technical relationships, hiring, and delivery across ambiguous enterprise environments. Partner with engagement and growth leaders, provide deliberate coaching and feedback, support customer deployments, and translate field insights into improvements for Mosaic, the company’s AI deployment toolkit.

Build production software and reusable AI-enabled products through customer-embedded delivery work. Develop prototypes into hardened, deployable products; define roadmaps, rollout plans, and adoption outcomes; contribute reusable capabilities to Mosaic; and maintain customer engagement after launch. The role requires strong Python and TypeScript skills, product judgment, communication, and comfort working in ambiguous environments with customer teams.

Founding data hire who builds end-to-end pipelines and models to convert messy enterprise data into AI-ready assets, defines data packs and ontologies, and builds internal tooling and automation so work compounds across customers. Works embedded with customer teams, partners with product and AI engineers, and makes architectural decisions about storage, orchestration, and data models.

Drive applied AI research (LLM post-training, RL, agentic modeling) embedded with customers. Design experiments, prototype and scale training pipelines, run customer-facing evaluations, translate research into production via partnership with engineers, and build infrastructure for distributed training to deliver measurable business value.