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.

• Bachelors 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.