Platform Engineer

Atlas Search; New York (NY); On-site; USD 140,000 - 200,000; Full time

Job summary

Atlas Search seeks a Platform Engineer to build secure, scalable AI platforms and developer tooling in a regulated financial services environment.

You’ll focus on infrastructure, cloud environments, data pipelines, APIs, and tools that enable Python-based AI apps using Azure AI Foundry, Anthropic Claude, and Azure OpenAI.

Qualifications

• 5+ years of infrastructure/platform engineering experience.
• Bachelor's degree in Computer Science, Computer Engineering, or related field; Master’s preferred.

Responsibilities

• Design, build, and operate enterprise AI platforms for Python-based applications.
• Build and manage Azure AI Foundry environments, model deployments, AI hubs, and access controls.
• Integrate Anthropic Claude API and Azure OpenAI with secure patterns, gateways, and cost controls.
• Develop internal tooling, SDKs, and scaffolding to accelerate AI app development.
• Create data pipelines with Azure Data Factory and Azure Databricks.

Skills

Python development

Azure

Terraform

Docker

Kubernetes

LLM APIs

Security & DevSecOps

Education

Bachelor's degree in CS/CE

Tools

Azure Data Factory

Azure Databricks

Azure OpenAI

Anthropic Claude

AKS

Terraform

Bicep

Docker

Kubernetes

Job description

We are seeking a Platform Engineer to build secure, scalable platforms and developer tooling that power enterprise AI initiatives within a highly regulated financial services environment.

This is a platform engineering role - not a machine learning research or model-training position. You’ll focus on building the infrastructure, cloud environments, data pipelines, APIs, and developer tools that enable engineering teams to rapidly develop and deploy Python-based AI applications using technologies such as Azure AI Foundry, Anthropic Claude, and Azure OpenAI.

You’ll work closely with application developers, data engineers, architects, security teams, and business stakeholders to build AI infrastructure that is scalable, secure, observable, and compliant.

What You'll Do

• Design, build, and operate enterprise AI platforms supporting Python-based AI applications.
• Build and manage Azure AI Foundry environments, including model deployments, AI hubs, project workspaces, and access controls.
• Integrate and operationalize Anthropic Claude API and Azure OpenAI using secure API patterns, gateways, rate limiting, monitoring, and cost controls.
• Develop internal developer tooling, SDKs, and scaffolding to accelerate AI application development.
• Build and maintain data pipelines using Azure Data Factory and Azure Databricks.
• Develop infrastructure supporting RAG applications, vector search, and document retrieval.
• Work with structured and unstructured data across Azure Data Lake, Azure SQL, Cosmos DB, and Azure AI Search.
• Build reliable data infrastructure to support enterprise AI applications.
• Provision and maintain secure, scalable infrastructure across Azure and AWS.
• Use Terraform and/or Bicep for Infrastructure-as-Code.
• Build CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Deploy and manage containerized workloads using Docker and Kubernetes/AKS.
• Implement Secure DevOps practices including secrets management, dependency scanning, and policy enforcement.

Security, Governance & Compliance

• Implement identity, access controls, encryption, and audit logging within a highly regulated environment.
• Build controls for MNPI data segregation and AI governance.
• Implement guardrails around AI API usage, including content filtering, usage tracking, and logging.
• Manage AI platform access through Azure Entra ID, RBAC, and managed identities.
• Partner with Security, Compliance, and Legal teams to enforce AI policies at the infrastructure level.
• Create architecture documentation, technical designs, runbooks, and operational documentation.
• Support developers building AI-powered applications and help troubleshoot platform issues.
• Partner with architects, data engineers, developers, and business stakeholders to translate requirements into scalable infrastructure solutions.

What We're Looking For

• 5+ years of experience in infrastructure engineering, cloud platform engineering, data engineering, or a related field.
• Bachelor's degree in Computer Science, Computer Engineering, or a related discipline; Master's degree is a plus.
• Experience building shared platforms, internal developer services, or enterprise infrastructure.
• Strong Azure experience, ideally including:
• AKS
• Strong Python development skills, including backend services, REST APIs (FastAPI/Flask), and automation.
• Experience with Terraform and/or Bicep, Docker, and Kubernetes.
• Production experience integrating LLM APIs, particularly Anthropic Claude and/or Azure OpenAI.
• Experience with RAG architectures, vector search, document processing, and retrieval systems.
• Familiarity with LangChain, Semantic Kernel, LangGraph, or AutoGen.
• Strong understanding of cloud security fundamentals including RBAC, managed identities, private endpoints, Key Vault, and network segmentation.
• Experience with DevSecOps, secrets management, SAST, and secure CI/CD.
• Familiarity with AWS technologies such as Bedrock, S3, and IAM.
• Experience with Microsoft Fabric, Databricks Unity Catalog, and/or Azure Synapse is a plus.
• Azure certifications such as AI-102, DP-203, or AZ-305 are a plus.
• Experience within investment banking or another highly regulated financial services environment is strongly preferred.