Job Description

Role Description

We are seeking a highly skilled Senior AI Tech Lead, this is a role requiring DevOps Engineering experience with a deep background in applied AI platforms, distributed systems, and intelligent automation. The ideal candidate will bring 10+ years of experience building and operating enterprise-scale platforms, with a proven track record of moving AI ideas from experimentation to secure, production-ready deployments in highly regulated environments. You will lead the design of robust cloud infrastructure and the operationalization of Large Language Models (LLMs) to drive business-focused innovation.

Key Responsibilities:

• Infrastructure Development:
  • Build and maintain Enterprise Feature Stores and real-time data lakes (BigQuery, Pub/Sub) to streamline predictive modeling and NLP workflows.
  • Design and implement resilient, secure multi-cloud architectures (GCP and Azure) using Terraform (IaC) to support high-availability AI operations.
• Model Operationalization & Agentic AI:
  • Operationalize ML models using Python, PySpark, and Kafka for both batch and real-time inference.
  • Leverage advanced orchestration frameworks such as LangChain, LangGraph, CrewAI, and Vertex AI Agent Builder to develop sophisticated agentic AI solutions.
  • Integrate secure inference APIs via gateways like APIGEE to ensure enterprise-grade connectivity.
• Deployment, Automation & MLOps:
  • Implement end-to-end CI/CD pipelines for automated model training, deployment, and seamless rollback capabilities.
  • Standardize LLMOps and MLOps observability practices using tools like LangSmith and Arize platforms.
  • Coordinate complex data and ML workflows using Cloud Composer (Airflow).
• Model Development/Tuning and Implementation:
  • Collaborate with data scientists to understand model objectives and translate them into technical specifications, applying appropriate Foundational models and frameworks to optimize effectiveness, response time, and cost for various use cases.
• Deployment and Automation:
  • Deploy AI models into multiple environments using CI/CD pipelines, ensuring seamless integration with existing systems.
  • Automate infrastructure provisioning and management processes using Infrastructure as Code (IaC) principles.
• Performance Monitoring & Governance:
  • Establish strong observability and data governance using tools like Grafana, OpenTelemetry, Splunk, or Arize to monitor pipeline health and model behavior.
  • Evaluate and integrate AI vendors (e.g., Snorkel, H2O.ai, Data Robot) for scalability, security, and cost-efficiency.
  • Ensure all deployments adhere to Responsible AI and compliance standards within regulated financial or retail environments.
• Collaboration & Leadership:
  • Lead Proof of Concepts (POCs) and pilots in controlled lab environments to validate emerging AI technologies.
  • Partner with cross-functional teams, including Data Science, Risk, Security, and Product, to align AI adoption with business strategy.
  • Provide technical mentorship to offshore and onshore engineering teams, ensuring high-performance standards and SLA compliance.
• Documentation and Best Practices:
  • Create and maintain comprehensive documentation for infrastructure setups, model development processes, and deployment workflows.
  • Establish and promote best practices for AI management and model development within the team.
• Security and Compliance:
  • Implement security measures to protect sensitive data and ensure compliance with industry regulations.
  • Work with security teams to address vulnerabilities and maintain a secure environment for AI operations.

Qualifications

• Bachelor’s or master’s degree in computer science, Engineering, or a related field.
• Proven experience in cloud infrastructure management, experience in GCP, Vertex AI, MLOps, and Terraform strongly preferred.
• Strong understanding of Large Language Models and experience in model development and deployment.
• Proficiency in programming languages such as Python, Java, or similar.
• Familiarity with CI/CD tools and practices.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.
• Strong communication and collaboration skills.
• Familiarity in using AutoML platforms such as Vertex AI AutoML, DataRobot, and open-source platforms such as Snorkel and H2O.ai.
• Nice to have Certification on Google Cloud platform such as GCP Cloud Engineer and/or GenAI leader.

Benefits

• Comprehensive benefits: Medical, dental, vision, 401(k) match, paid time off, PTO cash out.
• Support for you and your family: Family resources, EAP counseling sessions, access Headspace®, backup child and elder care, maternity/paternity leave, and more.
• Professional development programs: DaVita offers a variety of programs to help strong performers grow within their career and also offers on-demand virtual leadership and development courses through DaVita’s online training platform StarLearning.

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