Top Tech Jobs & Startup Jobs in NYC, NY

Drive technical sales and solution adoption through demonstrations, proofs of concept, hackathons, and architecture workshops. Partner with enterprise platform and engineering teams to design secure, scalable solutions using Microsoft Azure, Dynamics 365, Power Platform, and AI capabilities. Resolve technical blockers, influence solution architecture, support production deployments, build customer relationships, and represent Microsoft through technical thought leadership.

Leads and develops a team of Azure Solution Engineers serving public-sector customers. Coaches technical discovery, architecture design, demonstrations, workshops, prototypes, proofs of concept, and customer technical engagements. Drives Azure and AI growth, sales execution, pipeline progression, forecasting, CRM hygiene, executive relationships, and partner collaboration. Ensures secure, scalable solutions and effective transitions to deployment, adoption, and customer success.

Provides technical leadership for AI framework and model-serving initiatives at cloud scale. Owns architecture, roadmaps, performance optimization, benchmarking, observability, and multi-release execution across models, compilers, runtimes, services, GPUs, and silicon. Leads cross-team alignment, makes architectural decisions, mentors engineers, performs hands-on implementation and debugging, and drives measurable improvements in model onboarding, runtime performance, reliability, hardware utilization, and Azure capacity efficiency.

Build and verify FPGA-based networking acceleration for Microsoft Azure. Develop constrained-random SystemVerilog verification environments, test plans, test cases, assertions, sequences, constraints, and functional coverage. Automate test execution for CI/CD, collaborate with hardware and software teams using Agile methods, and occasionally support customer-reported hardware issues through on-call responsibilities.

Designs and operates controlled cyber-capability evaluations for frontier AI models and agentic systems. Builds vulnerable applications, cyber ranges, exploit-development targets, and evaluation harnesses; runs experiments; collects telemetry; analyzes model behavior and evaluation artifacts; and documents security findings. The role also develops sandboxing, containment, access, and secrets-management controls while collaborating with red-team operators, researchers, engineers, and Responsible AI stakeholders.

Lead technical pre-sales engagements for Microsoft 365 Copilot, Copilot Studio, AI agents, and cloud endpoint solutions. Deliver demonstrations, discovery sessions, whiteboarding, solution designs, and proof-of-concept support. Develop technical win strategies, address objections and blockers, collaborate with partners and internal teams, educate customers, and guide adoption while embedding governance, security, and compliance into proposed solutions.

Lead data science engagements with customers to acquire, clean, analyze, and model data; develop scalable operational models and evaluation methods; coach engineers on best practices; drive solution strategy, ethics, and industry thought leadership; write extensible code and collaborate across teams to deliver cloud-based AI solutions.

Lead architecture and hands-on development for Microsoft's virtualization platform, focusing on hypervisor and VMM capabilities. Design, implement, and optimize systems software across Windows, Linux, macOS, Azure, and containers. Improve performance, security, reliability, testing, and operational readiness; diagnose low-level hardware/software issues; enable virtualization on new silicon; mentor engineers; and influence platform strategy across teams and hardware partners.

Lead architecture and hands-on development of Microsoft's AI Safety Platform, building observability, detection, investigation, threat-hunting, and distributed data-processing capabilities. Design attack detection infrastructure, correlate high-volume telemetry, apply AI security research, conduct security and privacy reviews, and partner across engineering, science, and incident response teams. Mentor engineers and provide technical leadership for complex AI security systems.

Work on end-to-end AI performance for LLMs: benchmark and optimize inference on GPUs and Microsoft silicon, build tooling for performance insights and model porting, implement and test components in AI/DNN frameworks, and collaborate with internal and external partners to reduce hardware footprint and accelerate deployments.