Member of Technical Staff - 4 ( Devops - AI/ MLOPS, 8-10 yrs experience)

Hungry, Humble, Honest, with Heart.

The Opportunity

We are seeking a Senior to Staff-level DevSecOps Engineer (IC4+) to provide technical leadership across our secure software delivery and AI/ML platform infrastructure. This role is designed for a highly experienced individual contributor who can own architecture decisions, influence platform strategy, and drive DevSecOps excellence at scale.

You will design and operate secure, highly automated CI/CD and MLOps platforms, embed security controls throughout the SDLC, and partner closely with application, ML, platform, and security teams to ensure our systems meet the highest standards of security, reliability, performance, and compliance.

This is a hands-on role with broad organizational impact, requiring deep expertise in cloud-native infrastructure, Kubernetes security, automation, and modern DevSecOps practices.

About the Team

You will report to Sr. Manager Engineering, a highly approachable and supportive leader known for fostering trust, technical rigor, and a collaborative culture. The team values autonomy, accountability, and continuous improvement.

Your Role

As an IC4+, you will operate with significant autonomy and influence, owning complex systems end-to-end and shaping how DevSecOps and MLOps are practiced across the organization.

• Architect, build, and continuously evolve secure CI/CD platforms that support large-scale application and ML workloads, embedding security, compliance, and quality gates by default.
• Design and own infrastructure-as-code (IaC) foundations using Terraform, Ansible, or CloudFormation, emphasizing immutability, least privilege, and auditability.
• Lead Kubernetes security architecture, including RBAC design, workload isolation, network policies, secrets management, and runtime security controls.
• Design and operate observability platforms (metrics, logs, traces) using tools such as Coralogix, Prometheus, Grafana, and ELK, with a focus on early threat detection, incident response, and system health.
• Own reliability and performance of Kafka-based platforms, including capacity planning, monitoring, tuning, and failure mitigation.
• Design and implement automated ML / AI workflows (MLOps / LLMOps) that ensure experiment reproducibility, secure model lifecycle management, and scalable deployment.
• Integrate advanced security tooling (SAST, DAST, IAST, dependency and container scanning) into pipelines, enabling automated policy enforcement and remediation.
• Act as a technical mentor and force multiplier, raising the DevSecOps maturity of the team through reviews, design guidance, and best-practice advocacy.
• Partner cross-functionally with Security, Platform, AI/ML, and Product teams to translate risk, compliance, and performance requirements into pragmatic technical solutions.
• Continuously evaluate and introduce new technologies, frameworks, and patterns that improve security posture, developer velocity, and operational resilience.

What You Will Bring

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 4–12+ years of progressive experience in DevOps / DevSecOps / Platform Engineering roles, with clear ownership of production-grade systems.
• Proven experience designing and operating secure CI/CD platforms at scale.
• Strong proficiency in CI/CD tooling (Jenkins, GitLab CI/CD, CircleCI) and scripting/programming (Python, Bash, Go, or similar).
• Deep expertise in Infrastructure as Code, containerization, and Kubernetes internals and security.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP), including identity, networking, encryption, and native security services.
• Strong understanding of application and infrastructure security, including vulnerability management, secure supply chains, and runtime protections.
• Experience implementing and operating against compliance and security frameworks such as CIS benchmarks, SOC 2, GDPR, or HIPAA.
• Hands-on experience with MLOps/LLMOps, including designing model lifecycle pipelines, automating training and deployment workflows, and deploying scalable AI/ML systems in cloud-native environments.
• Ability to lead through influence, communicate complex technical concepts clearly, and drive alignment across engineering and security stakeholders.

Work Arrangement

Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Please speak with your recruiter for details. Additional team-specific guidance and norms will be provided by your manager.

--