Principal DevSecOps Engineer - AI
AI summary of the role
Principal DevSecOps Engineer embedding security across the AI lifecycle at a global fintech software leader.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Architect and implement secure, scalable CI/CD pipelines purpose-built for AI workloads including LLM-based and agentic AI systems.
- Shift security left by embedding SAST, SCA, container scanning, and policy-as-code into pipelines.
- Harden vector databases, retrieval APIs, and AI-serving infrastructure with platform engineering teams.
- Implement provenance, attestation, and traceability for datasets, training pipelines, and model artifacts.
What you’ll bring
- 8–10 years DevSecOps experience, ML/AI SecOps, supply chain security.
- Cloud security expertise in Azure, AWS, or GCP, particularly Kubernetes/Service Mesh and their AI services.
- Mandatory experience with Python/Go or similar programming language.
- Advanced knowledge of IaC (Terraform) and GitOps patterns.
Technologies
DevSecOps · ML/AI SecOps · Azure · AWS · GCP · Kubernetes · Service Mesh · Python · Go · Terraform · GitOps · Vault
About Finastra
Vista-backed banking software platform for lending, payments, and core banking, embedded in mission-critical systems across thousands of financial institutions.
Private Late · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Who are we? At Finastra, we’re a global leader in financial services software, dedicated to expanding access to financial services and shaping what’s next for the industry. Our technology powers mission‑critical solutions across Lending, Payments and Universal Banking, supporting over 7,000 customers, including 80% of the world’s top 50 banks, in more than 110 countries. A senior technical SME responsible for enabling secure, automated delivery of machine learning and AI workloads. This role operates at the intersection of AI/ML engineering, product development, platform infrastructure, and cybersecurity—embedding security controls across the entire AI lifecycle, including CI/CD pipelines, model registries, vector databases, MCP services, and agent‑based AI orchestration. Key Responsibilities: Secure AI Platform Engineering Architect and implement secure, scalable, and resilient
More from the job description
Who are we? At Finastra, we’re a global leader in financial services software, dedicated to expanding access to financial services and shaping what’s next for the industry. Our technology powers mission‑critical solutions across Lending, Payments and Universal Banking, supporting over 7,000 customers, including 80% of the world’s top 50 banks, in more than 110 countries. A senior technical SME responsible for enabling secure, automated delivery of machine learning and AI workloads. This role operates at the intersection of AI/ML engineering, product development, platform infrastructure, and cybersecurity—embedding security controls across the entire AI lifecycle, including CI/CD pipelines, model registries, vector databases, MCP services, and agent‑based AI orchestration. Key Responsibilities: Secure AI Platform Engineering Architect and implement secure, scalable, and resilient CI/CD pipeline’s purpose‑built for AI workloads, including LLM‑based and agentic AI systems. Automate secure build, deployment, and promotion workflows for AI workloads. ML/AI SecOps Integration Shift security left by embedding automated controls such as SAST, SCA, container/image scanning, and policy‑as‑code into pipelines. Implement AI‑specific security measures, including data‑poisoning safeguards, model integrity validation, and prompt‑injection mitigation. Infrastructure & Platform Securi [... source excerpt omitted ...] ails for responsible AI operations. Establish and maintain an AI Bill of Materials (AI‑BOM) to manage risk associated with third‑party models, components, and datasets. Required Qualifications: · 8–10 yrs DevSecOps experience, ML/AI SecOps, supply chain security. · Cloud Security expertise in securing Azure, AWS or GCP environment, particularly Kubernetes/Service Mesh, and their AI services · Mandatory Experience Python/Go, or similar programming language, along with advanced knowledge of IaC (Terraform) and GitOps patterns Preferred Skills: Experience with provenance/attestation frameworks (e.g., SLSA, Sigstore). Cloud security certifications (Azure, AWS, GCP). Hands‑on exper
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