Platform Engineer

Location : NYC In-person 5 days / week

Seniority : 5+ years of experience in platform engineering or infrastructure development

Compensation :

Salary : 200K to 275K

Competitive equity

Visa sponsorship not available (U.S. citizens only)

Employment Type : Full-time

About the Role

As a Platform Engineer , you will play a critical role in building and maintaining the infrastructure that powers core AI technologies. You will work at the intersection of AI, infrastructure, and enterprise systems , ensuring that platforms are reliable, scalable, and secure,  enabling product and AI teams to deliver cutting-edge AI-native applications.

This position offers an opportunity to own large-scale deployments , collaborate with cross-functional technical teams, and operate in regulated enterprise environments where reliability and performance are paramount.

️ Core Responsibilities

Design, build, and maintain the foundational infrastructure and services that power large-scale AI platforms.

Develop and optimize systems that enable seamless AI model integration into production environments.

Create and manage APIs, microservices, and data pipelines to support data processing, analytics, and AI model operations.

Build advanced Retrieval-Augmented Generation (RAG) systems, including optimized embeddings and indexing.

Implement and maintain security, compliance, and monitoring frameworks across all environments.

Collaborate with AI researchers and data scientists to improve MLOps frameworks for model deployment and lifecycle management.

Work closely with forward-deployed engineers to meet client-specific infrastructure needs.

Support product engineers by developing reusable platform components and scalable backend services.

Participate in architectural planning and contribute to the long-term technical vision of the platform.

Deploy and manage solutions across AWS GovCloud, on-prem, and multi-cloud environments (AWS, GCP, Azure).

Qualifications

Experience and Background

3+ years of software development experience focusing on scalable, distributed systems.

5+ years of experience building platforms supporting AI or ML model deployment and management.

Proven experience deploying across on-prem and cloud environments (AWS, GCP, Azure).

Hands-on on-prem deployment experience required.

Previous work in Series B to pre-IPO startups with high growth and evolving infrastructure.

Experience in regulated industries (finance, healthcare, government, or enterprise) is a strong plus.

Exposure to enterprise software deployment or consulting environments.

Bachelor's degree in computer science, Engineering, or related technical field.

Technical Skills

Deep expertise in AWS, with working knowledge of GCP and Azure.

Strong proficiency in Python, including deployment of scalable systems using FastAPI.

Solid understanding of microservices architecture, API design, and distributed systems.

Familiarity with data analytics platforms or business intelligence tools.

Working knowledge of machine learning concepts and MLOps infrastructure.

Experience with containerization (Docker, Kubernetes) and CI / CD automation.

Soft Skills and Attributes

Excellent communication and collaboration abilities.

Extreme ownership takes initiative and drives work to completion.

Strong problem-solving and creative thinking skills.

Reliable, detail-oriented, and highly accountable.