<p>We’re looking for a Senior Cloud Engineer to design, build, and operate secure, scalable infrastructure on Google Cloud Platform (GCP). You’ll lead with GKE for container orchestration, Infrastructure as Code (Terraform or Ansible) for repeatability, and scripting (Python, Shell/Bash) to automate everything from provisioning to observability. This role bridges architecture and hands-on delivery, partnering closely with DevOps, SRE, Security, and application teams.</p><p><br></p><p>What You’ll Do</p><ul><li><strong>Architect & implement</strong> highly available, cost-efficient GCP environments (VPCs, subnets, routing, load balancers, Cloud NAT, Cloud DNS, Cloud Storage, Cloud SQL/Spanner/BigQuery as applicable).</li><li><strong>Design, deploy, and operate GKE</strong> clusters (node pools, autoscaling, upgrades, ingress, CNI/CNI‑overlays, workload identity, network policies, pod security).</li><li><strong>Automate infrastructure</strong> with Terraform or Ansible (modules/roles, workspaces/environments, pipelines, policy-as-code).</li><li><strong>Build platform tooling</strong> and automation in Python/Shell/Bash (provisioning, configuration drift remediation, release packaging, operational runbooks).</li><li><strong>Implement observability</strong> (Cloud Monitoring/Logging, Prometheus/Grafana, OpenTelemetry) and actionable alerting/SLOs.</li><li><strong>Harden security</strong> (IAM least-privilege, service accounts, secrets management, private clusters, image scanning, workload identity, org policies).</li><li><strong>Enable CI/CD</strong> for apps and infra (Cloud Build/GitHub Actions/GitLab CI, artifact registries, blue/green or canary deployment strategies).</li><li><strong>Drive reliability</strong>—capacity planning, performance tuning, backup/DR strategies, incident response, root cause analysis, and postmortems.</li><li><strong>Mentor engineers</strong>, codify best practices, and contribute to architectural standards and roadmaps.</li></ul><p><br></p>
<p>We’re seeking a Senior AI/ML Engineer to build and scale real-time data pipelines, drive platform reliability, and lead core AI/ML engineering initiatives. You’ll work across teams to deliver high‑performance, secure, and cost‑efficient data and machine learning systems.</p><p><br></p><p>Responsibilities:</p><ul><li>Architect and maintain scalable data pipelines (GCP, Kafka, Flink).</li><li>Own reliability, observability, and performance of the data/ML platform.</li><li>Optimize infrastructure performance and cloud costs.</li><li>Standardize data modeling and testing (dbt or similar).</li><li>Implement Infrastructure as Code and automation best practices.</li><li>Ensure security, governance, and compliance across data systems.</li><li>Lead cross-functional initiatives and mentor engineering peers.</li><li>Drive continuous improvement in tools, processes, and standards.</li></ul><p><br></p><p><br></p>
We are seeking a hands-on Senior Enterprise Architect in Artificial Intelligence (AI) to join our global Enterprise Architecture team. This role blends deep technical expertise with architectural design and practical implementation to drive AI-powered transformation initiatives.<br><br>As part of a forward-thinking global technology team, you’ll collaborate across business, data, and product functions to design and implement AI/ML solutions that enable digital products and services.<br><br>Key Responsibilities<br><br>Design and architect enterprise-scale AI/ML solutions across areas such as Machine Learning, Generative AI, Deep Learning, Virtual Assistants, and Cognitive Services (Vision/Image, Text/Language processing).<br>Develop and communicate AI roadmaps, future-state architectures, and design artifacts.<br>Rapidly prototype and build proof-of-concepts (PoCs) and MVPs for AI models and algorithms.<br>Evaluate and recommend AI/ML tools, platforms, and frameworks; conduct ROI analysis.<br>Experiment with and fine-tune LLMs, train custom models, and assess performance metrics.<br>Perform data exploration, cleansing, and feature engineering to prepare datasets for model training.<br>Guide and mentor engineering and data science teams through AI/ML solution design, deployment, and integration into enterprise workflows.<br>Continuously scan industry innovations and apply emerging AI/ML technologies to business problems.<br>What We’re Looking For<br><br>Strong technical and business acumen in creating technology-driven solutions.<br>Passion for experimenting with and adopting emerging AI/ML technologies.<br>Excellent communication and influencing skills; ability to present complex technical concepts to both technical and non-technical audiences.<br>Proven ability to balance timeliness, cost, and quality in solution design.<br>Experience leading digital transformation, target operating models, and performance improvement initiatives.<br>Qualifications<br><br>Bachelor’s degree in STEM or related field (MBA a plus).<br>5+ years in AI/ML solution architecture, prototyping, and experimentation.<br>5+ years working with AWS and/or Azure data, analytics, and AI services.<br>3+ years of experience with data science tools and frameworks.<br>Recent, hands-on experience with Generative AI, LLMs, and Agentic AI platforms.<br>Knowledge of cloud-native services (data storage, compute, networking, security).<br>Strong understanding of statistical methods, data preprocessing, and feature engineering.
