Sr. Data & AI Platform Engineer

Soni Resources

$175K — $215K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science or related field.
  • 8+ years of experience in cloud infrastructure, platform engineering, DevOps, or data engineering.
  • Experience building enterprise platforms or shared developer services.
  • Strong expertise with Azure cloud technologies, including AI Foundry, Data Factory, and Databricks.
  • Proficient in Python development and REST API frameworks like FastAPI or Flask.
  • Experience with infrastructure as code tools such as Terraform and/or Bicep.
  • Knowledge of RAG architectures and integrating LLM services.

Responsibilities

  • Design and support enterprise AI platforms for Python applications.
  • Manage and configure Azure AI Foundry, including project workspaces and model deployments.
  • Integrate Azure OpenAI APIs with secure authentication and monitoring.
  • Develop developer tools and automation for AI application delivery.
  • Build data pipelines utilizing Azure Data Factory and Azure Databricks.
  • Implement infrastructure for vector search and document retrieval.
  • Provision Azure infrastructure with Terraform or Bicep and build CI/CD pipelines.

Benefits

  • Flexible working hours and remote work options.
  • Professional development opportunities, including certifications.
  • Collaborative team environment with cross-functional teams.
  • Access to advanced tools and technologies in AI and cloud computing.
Full Job Description
Senior Data & AI Platform Engineer

Position Overview

Our client is seeking a Senior Data & AI Platform Engineer to design, build, and support secure, scalable cloud infrastructure that enables enterprise AI initiatives. This platform engineering role focuses on building the infrastructure, developer tooling, and data platforms that allow engineering teams to rapidly develop and deploy AI-powered Python applications. The ideal candidate has strong experience with Azure cloud technologies, data engineering, infrastructure automation, DevOps, and AI platform services.

Responsibilities
  • Design, build, and support enterprise AI platforms for Python-based AI applications.
  • Configure and manage Azure AI Foundry, including AI hubs, project workspaces, model deployments, and access controls.
  • Integrate Azure OpenAI and third-party LLM APIs using secure authentication, API management, monitoring, and cost controls.
  • Develop reusable developer tools, templates, and automation to accelerate AI application delivery.
  • Build and maintain data pipelines using Azure Data Factory and Azure Databricks.
  • Implement vector search and document retrieval infrastructure to support RAG applications.
  • Manage Azure Data Lake, Azure SQL, Cosmos DB, and other enterprise data platforms.
  • Provision and maintain Azure infrastructure using Terraform and/or Bicep, with exposure to AWS environments.
  • Build CI/CD pipelines using Azure DevOps and/or GitHub Actions and manage containerized workloads with Docker and Kubernetes (AKS).
  • Implement DevSecOps best practices, including secrets management, security scanning, and policy enforcement.
  • Partner with engineering, architecture, security, and business teams to deliver secure, scalable AI solutions.
  • Create technical documentation, architecture diagrams, and operational runbooks.


Qualifications
  • Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or a related field.
  • 8+ years of experience in cloud infrastructure, platform engineering, DevOps, or data engineering.
  • Experience building enterprise platforms or shared developer services.
  • Strong expertise with Azure AI Foundry, Azure Data Factory, Azure Databricks, AKS, Azure API Management, Azure Key Vault, and Azure Entra ID.
  • Strong Python development skills, including REST APIs (FastAPI or Flask) and automation scripting.
  • Experience with Terraform and/or Bicep, Docker, Kubernetes, and CI/CD pipelines.
  • Experience integrating enterprise LLM services such as Azure OpenAI and Anthropic Claude APIs.
  • Knowledge of RAG architectures, vector search, and AI frameworks such as LangChain or Semantic Kernel.
  • Strong understanding of cloud security, identity management, DevSecOps, and enterprise governance.
  • Preferred: Experience with AWS, Microsoft Fabric, Azure Synapse, Databricks Unity Catalog, Azure certifications (AI-102, DP-203, AZ-305), or experience supporting highly regulated enterprise environments.


Compensation: $175,000 to $215,000 annually
Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications.

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