Senior DevSecOps Lead: Artifacts & AI Security

eFinancialCareers

Greater London

Hybrid

GBP 90,000 - 140,000

Full time

7 days ago

Be an early applicant

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Job summary

eFinancialCareers is seeking a DevSecOps Engineer focused on artifact management and software supply chain security. You will secure and govern artifact repositories across cloud and hybrid environments, integrating with CI/CD pipelines.

Ideal candidates have 3-6 years in DevSecOps, hands-on with JFrog Artifactory, and experience with GitHub, Jenkins, and Azure DevOps. Knowledge of AI/ML security and Responsible AI principles is a plus.

Qualifications

3-6 years of experience in DevSecOps, platform security, or software supply chain security.
Hands-on with JFrog Artifactory, including deployment and enterprise architecture.
Experience designing package curation and promotion models.
Foundational understanding of AI/ML and Generative AI concepts, including LLMs.
Knowledge of AI/ML security risks such as prompt injection, data leakage.
Experience integrating AI or ML components into applications or pipelines.
Familiarity with Responsible AI principles and AI governance frameworks.
Experience implementing waiver and approval workflows for dependencies and artifacts.
Strong understanding of application security and dependency risk management.
Hands-on experience integrating repositories with GitHub, Jenkins, and Azure DevOps pipelines.
Experience working in cloud environments (Azure preferred; AWS/GCP acceptable).
Proficiency with automation and scripting (Python, Groovy, Terraform).
Knowledge of modern SDLC and DevSecOps operating models.

Responsibilities

Design, deploy, and operate enterprise artifact repository platforms.
Define and enforce package curation, promotion, and trust models.
Implement and govern waiver and approval workflows for dependencies and artifacts.
Partner with AppSec, platform, and engineering teams to standardize secure patterns.
Define and maintain repository architectures supporting multiple environments.
Enforce policies for artifact immutability, provenance, versioning, and trusted sourcing.
Integrate artifact repositories into CI/CD pipelines (GitHub, Jenkins, Azure DevOps).
Embed security controls for AI/ML and GenAI workloads within pipelines.
Define secure usage patterns for LLMs and data protection.
Monitor AI/ML risk and integration with third-party models and APIs.
Develop automation and policy-as-code for artifact lifecycle management.