Top Tech Jobs & Startup Jobs in NYC, NY

Lead end-to-end UX design: create wireframes, prototypes and mock-ups (Figma); conduct user research and usability testing; use data and AI tools to inform decisions; present to stakeholders; facilitate workshops; integrate design systems into engineering workflows and ensure smooth handoffs.

Operate and monitor ML/AI models and agentic systems in production. Build AI observability, logging, tracing, and evaluation pipelines. Monitor LLM outputs, detect drift and model degradation, and maintain data/feature pipelines. Develop CI/CD, model versioning, experiment tracking, and automate alerts and incident remediation while collaborating with data scientists and platform teams.

Build and deploy generative AI solutions: develop production-grade Python code, LLM-based systems, agent frameworks, RAG pipelines with vector databases, APIs, cloud deployments, and MLOps practices while ensuring model evaluation, guardrails, and observability.

Design, build, and deploy agentic AI and multi-agent systems using LangChain/LangGraph and ADKs. Implement LLM orchestration, RAG pipelines, vector DBs, React-based AI interfaces, and production-grade infrastructure with observability, security, and optimization.

Lead design, delivery and implementation of scalable production software across a complex, regulated environment. Drive DevOps/CI-CD, GitOps, containerization, Kubernetes and IaC adoption, improve incident/problem management and observability, coach teams, implement Agile, and manage senior stakeholders to ensure reliable, high-scale services.

Design and implement data federation and lakehouse architectures, build scalable ETL/ELT pipelines with Python and Spark, optimize performance across federated queries, manage Delta/Iceberg/Hudi tables, and enforce governance, security, and access controls for analytics and AI teams.

Lead migration from AEM 6.5 to AEMaaCS: assess implementations, architect cloud-native components, manage content migration with CTT, redesign dispatcher, implement CI/CD via Adobe Cloud Manager, modernize integrations, train teams, and provide post-migration support and technical documentation.

Own product vision and roadmap for a cloud-native data platform on GCP. Translate business needs into epics and user stories, prioritize ETL/ELT, databases, streaming, and BI work, coordinate onshore/offshore teams, ensure data governance, quality, and analytics readiness, and drive adoption of Snowflake and DOMO-based analytics.

Lead design, development, and deployment of production-grade Generative AI applications (LLM-based chatbots, agents, RAG systems). Hands-on coding in Python, integrate and benchmark models, build ingestion and vector retrieval pipelines, design architecture for performance and cost, mentor engineers, and implement AI governance, safety, and monitoring.

Translate ambiguous business problems into AI-native product opportunities. Develop future-state, prompt-driven experiences, hyper-personalized journeys, and strategic narratives. Lead cross-functional teams, benchmark AI product trends, and present executive-ready transformation roadmaps.