Top Senior Platform Engineer Jobs in NYC, NY

Design, deploy, secure, automate, and operate enterprise MongoDB platforms across on-premises infrastructure and MongoDB Atlas. Responsibilities include replica sets, sharding, high availability, disaster recovery, backup and recovery, performance tuning, monitoring, security controls, migrations, incident response, and lifecycle management. The role partners with application, cloud, infrastructure, security, and SRE teams; develops operational standards and automation; supports mission-critical environments; and provides technical leadership and mentorship.

Senior full-stack engineer responsible for designing, building, testing, deploying, and supporting scalable lead capture, routing, tracking, and advisor-facing platform features. The role is approximately 70% frontend and 30% backend, using NestJS, Node.js, React, AWS, databases, event-driven architectures, CI/CD, automated testing, analytics, observability, and LLM-backed functionality. Responsibilities include architecture, production troubleshooting, performance optimization, technical planning, code reviews, documentation, and mentoring.

Own and improve Localize’s AWS and Cloudflare infrastructure, databases, platform tooling, deployments, monitoring, security, and SDLC practices. Manage Redis and MongoDB reliability, optimize performance and costs, strengthen CI/CD, lead incident response, support SOC 2 Type II compliance, and maintain disaster recovery capabilities. Partner with product engineers and leadership to prioritize infrastructure improvements, communicate tradeoffs, and improve customer-facing reliability, security, and delivery speed.

Build and operate backend platform services for query execution, journey orchestration, data transformation, and export delivery. Design APIs and integrations with cloud data warehouses, improve reliability and observability, support real-time capabilities, participate in on-call, resolve customer and production issues, and develop automation and shared components. Mentor engineers and help build AI-powered products.

Lead the architecture and development of enterprise AI platforms, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, scalability, safety, and transparency. Set long-term technical strategy, drive organization-wide standards, lead platform initiatives, partner cross-functionally, and mentor senior engineering and research leaders.

Build and lead a scalable platform engineering function spanning CI/CD, infrastructure, observability, developer tooling, environments, and production operations. Develop internal tools, reusable automation, paved roads, and AI-assisted workflows that improve developer experience, delivery reliability, and engineering productivity. Partner across teams, guide architecture and standards, measure DORA and DX metrics, and shape the platform roadmap while providing hands-on technical leadership.

Design and operate Go backend services for listing and settling prediction-market contracts. Lead migration from Python and Airflow, build provider data pipelines, reconcile events idempotently, and develop resilient settlement logic for failures and corrections. Establish engineering standards, make architecture decisions, mentor engineers, participate in on-call and incident response, and collaborate with trading, compliance, operations, and product teams.

Hands-on technical lead designing, building, and optimizing high-performance Linux compute platforms for low-latency electronic trading. Responsibilities include kernel- and hardware-level performance tuning, containerization, IaC and CI/CD design, automation and tooling development, vendor interfacing, AI-assisted engineering governance, and mentoring cross-functional engineering teams to deliver reliable, low-latency infrastructure.

Build and operate cloud infrastructure for an AI platform: design Terraform modules, run production Kubernetes, manage CI/CD and release engineering, implement observability and SLOs, enforce security/compliance controls, manage secrets and certificates, and support incident response and platform readiness.

Build and operate production AI agents, agentic workflows, MCP servers, and CX applications. Develop Python and TypeScript services, AWS infrastructure, integrations, testing, observability, security controls, and CI/CD pipelines. Partner with Customer Success and other CX teams to prototype solutions, translate workflows into technical plans, and deliver reusable platforms. Mentor engineers and non-engineers, document systems, establish governance, and support reliable handoff and shared ownership.

Develop and maintain core Elasticsearch infrastructure, scalable APIs, CI/CD workflows, observability, and cloud operations. The role focuses on improving developer productivity through automation and AI-enabled workflows, resolving complex performance and concurrency issues, and leading cross-team technical projects. Responsibilities include end-to-end operational investigations, supporting difficult customer issues, and collaborating across distributed engineering teams and open-source projects.

Leads the design, operation, and evolution of global Azure and multi-cloud infrastructure for enterprise SaaS platforms. Responsibilities include Infrastructure-as-Code, cloud networking, identity and governance, disaster recovery, high availability, security, automation, developer platform improvements, and operational excellence. The role provides technical leadership, mentorship, architecture guidance, and cross-functional collaboration with security, compliance, operations, and engineering teams.

Build and operate shared AI platform capabilities, including SDKs, APIs, agent infrastructure, durable workflows, model integrations, retrieval, evaluation, and debugging tools. The role focuses on reliability, observability, performance, secure customer-data handling, and turning AI experiments into reusable production capabilities. Responsibilities also include partnering with product teams, driving adoption, diagnosing AI failures, and mentoring or leading broader technical initiatives.

Set the multi-year technical direction for the Builder Platform, leading agent platforms, AI infrastructure, developer infrastructure, and productivity engineering. Establish governance, architecture, standards, metrics, and adoption strategies across the company. Partner with engineering and business leaders to prioritize AI opportunities, improve developer productivity, guide customer-zero feedback into products and open-source frameworks, mentor technical leaders, and reduce operational burden through systemic improvements.

Build and operate Temporal’s internal Agent Platform, AI infrastructure, developer infrastructure, agents, workflows, and engineering tools. The role includes establishing governance and reliability controls, partnering cross-functionally to accelerate work, driving adoption, measuring usage and productivity, contributing to open-source architectures, and participating in on-call support.

Lead enterprise customer deployments of Quilter’s AI-powered PCB design platform across cloud and customer-managed environments. Integrate Kubernetes, cloud infrastructure, networking, storage, access controls, and OIDC-based SSO. Troubleshoot application and infrastructure issues, create deployment automation and diagnostics, support upgrades and rollbacks, document operating procedures, and coordinate customer needs with engineering and go-to-market teams.

Administer and engineer enterprise observability platforms spanning infrastructure, applications, cloud resources, and telemetry. Lead technical onboarding, monitoring design, alerting, dashboards, automation, integrations, troubleshooting, capacity planning, licensing optimization, upgrades, and migrations. Establish standards and documentation, collaborate with vendors and procurement, and mentor engineers. The role requires strong systems thinking, cloud and production support experience, scripting or infrastructure-as-code expertise, and the ability to resolve complex reliability and performance issues.

Own PushPress’s data platform, including ingestion, orchestration, cloud warehouse performance, governance, privacy, data quality, monitoring, and AI-ready data foundations. Build reliable pipelines integrating product, payment, and third-party data; establish data contracts, access controls, auditability, and semantic definitions; support real-time analytics and trustworthy reporting. Partner with Engineering, Data, and AI teams while maintaining infrastructure, incident response, documentation, and operational runbooks.

Design and build scalable streaming, messaging, and storage platforms supporting StubHub’s distributed systems. Develop SDKs, shared services, tools, and cross-language runtime environments; architect high-performance internal services; and improve scalability, reliability, and performance. Serve as a subject matter expert in distributed caching and messaging, collaborate with engineering teams, lead platform initiatives, own projects through production, and mentor junior engineers.

Manage and improve automated Linux infrastructure and on-premises Kubernetes platforms. Develop system software, middleware, APIs, and automation using Python, Bash, and configuration management tools. Maintain packages and repositories, support CI/CD integration, troubleshoot operating system, network, and container issues, implement security hardening, and participate in on-call support. Collaborate with application support, development, and security teams to ensure reliable, secure, and scalable infrastructure.

Lead the design and delivery of complex insurance infrastructure projects, owning problems from definition through production. Build and maintain scalable distributed systems, improve reliability and performance across product, infrastructure, and data, optimize user experiences, and mentor engineers. The role requires strong judgment, independent ownership, API development expertise, and experience with Python or Go, AWS, infrastructure as code, and production systems at scale.

Analyzes exposure risks across databases and data platforms, including permissions, access models, configurations, storage, encryption, and service-to-service access. Investigates attack paths, validates risks using queries and logs, prioritizes issues by exploitability and business impact, and partners with database, cloud, platform, engineering, and cybersecurity teams on remediation and preventative controls.

Build and guide data platform capabilities supporting marketing, finance, analytics, and data science. Develop data collection, integration, scoring, experimentation, analytics, and infrastructure solutions; contribute code, lead cross-functional technical initiatives, improve system resiliency through incident response, and establish engineering standards. Partner with business and technical stakeholders to define strategy and long-term roadmaps.

Design and build reusable backend platform services, libraries, frameworks, integrations, and AWS infrastructure abstractions. Establish reliability, security, observability, testing, compatibility, and deployment standards for consuming teams. Direct AI-agent implementation through specifications and contracts, review generated and human code, manage incidents, and drive production adoption of shared platform capabilities.

Owns an Agentic AI platform across CI/CD, AWS infrastructure, Kubernetes operations, observability, security, and runtime reliability. Builds delivery pipelines, automated testing and quality gates, EKS environments, infrastructure-as-code, monitoring and alerting, synthetic health checks, and runtime security testing. The role requires strong operational ownership, troubleshooting, secure supply-chain practices, audit readiness, and platform resilience in regulated or mission-focused environments.