Top Tech Jobs & Startup Jobs in NYC, NY

Lead the data migration practice and analysts, owning complex customer migrations from legacy legal and accounting systems through go-live. Build C# and SQL conversion tooling, troubleshoot databases and cloud servers, document migration logic, and guide nontechnical customers through exports. Support AWS and Azure SOC 2 controls, data residency, retention, and AI-assisted development.

Build and maintain C# and SQL data migration tooling, staging schemas, scripts, and cloud automation. Lead complex legal accounting migrations, troubleshoot databases and cloud servers, write custom SQL, and support migration analysts with technical guidance. Create client-facing documentation, map and validate data, enforce SOC 2 and data residency controls across AWS and Azure, and use AI coding tools to automate recurring work.

Lead a player-coach engineering team building AI agents that create, launch, and optimize marketing campaigns. Own technical strategy, roadmap delivery, architecture, reliability, hiring, and team development. Solve problems involving content generation, customer context management, marketing insights, and campaign orchestration across advertising and lifecycle platforms.

Own the end-to-end design and implementation of Loancrate’s user experience, from Figma wireframes through accessible React and TypeScript components. Build and maintain a scalable shadcn/ui design system and component library, translate mortgage workflows into intuitive experiences, and establish consistent visual and interaction standards in partnership with product and engineering.

Build and support complex features across C#/.NET back-end services and React front ends. Responsibilities include technical design, API and data modeling, secure and tested coding, production troubleshooting, code reviews, mentoring, documentation, and improving engineering practices. Collaborate with Product, QA, DevOps, Technical Leads, and architecture teams while balancing delivery, maintainability, performance, accessibility, observability, and security.

Design and deploy production AI/ML systems, including data pipelines, RAG systems, agentic workflows, model integrations, APIs, observability, evaluations, guardrails, and cost optimization. Collaborate with product, design, and client stakeholders while contributing to architecture, code reviews, testing, deployment, and technical strategy. Build reliable, secure, scalable systems using modern LLM and cloud technologies.

Implements a scientific software platform for enterprise R&D customers by migrating data, modeling experimental workflows, and supporting customer meetings. The role interprets scientific datasets, collaborates with chemists and researchers, supports enterprise rollouts, manages smaller accounts, and shares customer feedback with product and engineering teams. Candidates need STEM training, laboratory research experience, fluent French, technical curiosity, customer confidence, and strong data skills.

Lead the architecture and hands-on development of an AI-enabled data migration platform for legal software. Own extraction, transformation, orchestration, data quality, observability, and scalable go-live workflows. Partner with product management to define roadmap priorities, lead a focused engineering team, make architectural decisions, contribute code, and apply AI to migration assessment, mapping, validation, and automation.

Leads and grows a distributed software engineering team building a scalable cloud data and analytics platform. Owns architecture, data modeling, technical delivery, roadmaps, product collaboration, agile planning, quality standards, security alignment, vendor relationships, and engineering KPIs. The role remains hands-on with coding, code reviews, documentation, data architecture, deployment, and development of SaaS data products using Azure or AWS, Microsoft Fabric or Snowflake, and Power BI.

Leads multiple engineering teams delivering AI-powered data connectivity solutions. Owns execution, delivery, technical direction, operational reliability, and cross-team coordination. Develops engineering talent through coaching, hiring, and performance management while partnering with Product and Engineering leadership on priorities and organizational planning. Guides architecture, cloud-native development, incident response, SLOs, and AI-assisted software development practices. Requires strong Java/Kotlin expertise, cloud architecture experience, and technical judgment across distributed systems.