Description

You will lead the architecture, build, and scaling of enterprise-grade AI/ML platforms, driving technical strategy and mentoring engineering teams.

This role is remote.

Responsibilities

• Design and implement scalable AI/ML platforms supporting model training, deployment, monitoring, and lifecycle management.
• Build and maintain AWS landing zones, networking, IAM, and Snowflake account/role structures with strict security governance.
• Enable AI engineers with reusable platform components, including Bedrock setup, Cortex enablement, and secure data zones.
• Drive infrastructure code reviews, environment promotions, and MLOps best practices for CI/CD pipelines.
• Collaborate with product, data science, and business stakeholders to align AI platform capabilities with organizational goals.

Required Skills

• 14+ years of software engineering experience, with 5+ years focused on AI/ML platforms.
• Strong hands-on experience with AWS infrastructure (VPC, IAM, KMS, Private Link, Transit Gateway, S3, Lambda, ECS/EKS).
• Snowflake administration skills: RBAC, network policies, masking, row access policies, warehouses, and resource monitors.
• Proficiency in IaC (Terraform/CloudFormation) and CI/CD tools (CodePipeline, GitHub Actions).
• Expertise in cloud platforms (Azure, AWS, GCP) and container orchestration (Kubernetes, Docker).
• Strong knowledge of MLOps frameworks (Kubeflow, MLflow, SageMaker, Vertex AI).
• Proficiency in Python, Java, or Go.
• Deep understanding of distributed systems, data pipelines, and model deployment at scale.
• Experience delivering AI/GenAI use cases for financial services.

Preferred Skills

• Familiarity with data engineering tools (Spark, Kafka, Databricks).
• Exposure to generative AI and LLM deployment frameworks.
• Track record of leading global teams and delivering complex AI initiatives.

Key Skills

Education

Any Graduate