Senior AI Platform Engineer (Data and Analytics Cloud Engineer)

Quick Facts

• Language Fluency: English (Required)

Description

Designs, develops, and implements AI capabilities and data-driven solutions and leads large technical initiatives to address complex business challenges. Builds advanced AI models and data architectures to improve system accuracy, efficiency, and resilience, applying AI and analytics to generate actionable insights that support strategic decisions.

Essential Duties And Responsibilities

• Design, build, and execute the AI/ML and GenAI platform strategy aligned to enterprise architecture, security, and risk standards.
• Own the engineering and lifecycle management of AI/ML platform components (development workspaces, training/inference patterns, model registry, feature storage patterns, experiment tracking, prompt/version management, retrieval-augmented generation (RAG) enablement, reusable templates) for safe and deliberate organizational consumption.
• Establish and champion DevSecOps practices for platform delivery, including GitLab source control, build automation, and CI/CD pipelines for infrastructure and application deployments.
• Deploy infrastructure as code (IaC) to the cloud using Terraform modules and pipelines; define standards for environments, networking, identity, secrets, encryption, logging, and configuration management.
• Partner with Cybersecurity, Risk, and other 2nd line of defense teams to implement and evidence security controls (IAM least privilege, network segmentation, encryption, vulnerability management, audit logging, policy-as-code) across platform services.
• Implement governance patterns for AI/ML and GenAI (model and prompt lifecycle controls, lineage/traceability for data/prompts/outputs, approvals, change management, risk assessments, operational readiness) aligned to enterprise data governance and regulatory obligations.
• Provide technical leadership and hands-on engineering to solve complex platform problems (performance, reliability, scalability, cost, security), and guide engineers through designs, reviews, and delivery.
• Build platform reliability through automation and observability (monitoring, logging, tracing, SLOs) and partner with production support to reduce toil and improve time to recover.
• Enable self-service platform consumption via standardized APIs, reusable pipelines, templates, and documentation; in an Agile environment, may serve as an Agile/DevSecOps champion.

Requirements

Required Qualifications:

• Bachelor’s degree in Computer Science, Data Science, AI, Software Engineering, or related field.
• Minimum of 7 years of professional experience in AI and data.
• Strong knowledge of AI models, data architectures, and analytics methodologies.

Preferred Qualifications:

• Master’s degree and/or 8+ years of progressive experience delivering complex cloud platforms, preferably supporting AI/ML or analytics workloads at enterprise scale.
• Experience building AI/ML platforms and/or MLOps capabilities (training/inference automation, model packaging and deployment, model registry, experiment tracking, operational monitoring).
• Experience with container platforms and orchestration (Kubernetes/EKS), API enablement, and modern ML tooling (Python ecosystem) to operationalize models and GenAI services.
• Deep expertise in AWS (compute, networking, security/IAM, logging/monitoring, managed services) and moderate experience with Azure services and deployment patterns.
• Hands-on DevOps/DevSecOps experience building CI/CD pipelines (GitLab) with automated testing, security scanning, artifact management, and controlled deployments.
• Strong infrastructure-as-code experience deploying cloud components using Terraform; ability to build reusable modules and enforce standards/guardrails.
• Relevant cloud and security certifications (preferred), such as AWS Solutions Architect/DevOps Engineer, AWS Security Specialty, Azure Administrator/Architect, and/or Terraform certification; strong mentoring/coaching skills for distributed onshore/offshore teams.

Benefits

• Medical, dental, vision
• Life insurance, disability, accidental death and dismemberment
• Tax-preferred savings accounts
• 401k plan
• No less than 10 days of vacation (prorated based on hire date and status)
• 10 sick days (prorated)
• Paid holidays
• Depending on position/division: defined benefit pension plan, restricted stock units, and/or deferred compensation plan