AI Solutions Engineer (Senior / Principal)

Job description

## RAVL helps technologists accelerate their careers. At RAVL, we connect strategy with execution, care deeply about the people we work with, and measure success by the lasting impact we leave behind. Our purpose is to build a team that puts real, sustainable business outcomes at the core of everything we do. We're here to leave our clients better than we found them—and to create a place where our people are proud to **Build. Better.** ## ## About the Role We're looking for a **Senior / Principal AI SDLC Engineer** to help our financial services clients modernize how software is built, secured, and delivered in an AI-enabled world. This is a **DevSecOps and developer platform engineering role** focused on enabling both engineers and AI coding agents to deliver software safely within highly regulated enterprise environments. You'll build the secure delivery foundations that allow teams to create, review, test, approve, deploy, and operate software with confidence while meeting governance, security, and audit requirements. Rather than building customer-facing AI applications, you'll design and evolve the engineering platform that makes enterprise AI development scalable, secure, and repeatable. As a Senior or Principal engineer, you'll influence platform architecture, partner closely with engineering, security, and risk stakeholders, and help shape next-generation software delivery practices for some of Canada's leading financial institutions. ### What does success look like in this role? - Build and ship agents and AI apps on Vertex AI (Agent Builder, Gemini, Vector Search, Model Garden), served on GKE or Cloud Run. - Integrate with Azure enterprise services: IAM and Workload Identity, Secret Manager, Pub/Sub, and Cloud Logging and Monitoring. - Design and build self-service developer platforms that enable secure, policy-driven software delivery across enterprise environments. - Develop automated delivery pipelines that integrate version control, CI/CD, Infrastructure as Code, identity, secrets management, artifact repositories, and observability. - Design secure operating models for AI coding agents, including controlled access to repositories, tools, execution environments, permissions, context, approvals, and audit trails. - Strengthen the software supply chain through automated security practices including SAST, SCA, secrets detection, SBOM generation, artifact signing, provenance, dependency governance, and controlled promotion. - Automate governance requirements such as separation of duties, approvals, traceability, retention, evidence collection, and compliance reporting without slowing delivery. - Build risk-based deployment strategies including progressive delivery, release approvals, rollback capabilities, and automated release evidence for both deterministic and AI-assisted development workflows. - Create reusable platform templates, paved roads, documentation, and engineering standards that make secure software delivery the easiest path for development teams. - Lead architecture discussions, mentor engineers, and contribute reusable platform capabilities that strengthen both client delivery and RAVL's engineering practice. - Collaborate with engineering, security, risk, audit, and operations teams to balance delivery velocity with enterprise governance requirements. ### Sounds great, do my skills fit? We're looking for engineers who combine deep platform engineering expertise with modern DevSecOps practices and a passion for improving the software development lifecycle. **Required** - Hands-on Vertex AI for agent and LLM work (Gemini, Agent Builder, Vector Search), plus GKE or Cloud Run serving. - Strong experience building and operating modern DevSecOps platforms including CI/CD pipelines, Infrastructure as Code, identity and access management, secrets management, secure execution environments, and observability platforms. - Practical experience implementing software supply chain security, including SAST, SCA, secrets scanning, SBOM generation, artifact signing, provenance, dependency governance, and secure artifact promotion. - Experience implementing policy-as-code and designing secure authorization models for automated development workflows and AI-assisted engineering tools. - Strong understanding of enterprise change management, release management, auditability, and traceability across the full software delivery lifecycle. - Experience building reliable engineering platforms that emphasize automation, developer experience, operational resilience, and governance. - Strong understanding of cloud-native architecture, container platforms, and modern infrastructure automation. - Experience collaborating with engineering, security, compliance, and risk stakeholders to implement practical governance in regulated environments. - For Senior and Principal candidates, demonstrated experience leading platform architecture, mentoring engineers, influencing engineering strategy, and driving adoption across multiple delivery teams. ### Nice to Have - Experience working within banking, insurance, wealth management, or other highly regulated industries. - Experience with GitHub Enterprise, GitLab, Azure DevOps, Backstage, Harness, Argo CD, Tekton, or similar enterprise developer platforms. - Experience with HashiCorp Vault, Open Policy Agent (OPA), Conftest, SonarQube, Snyk, Checkmarx, Veracode, JFrog Artifactory, or equivalent security tooling. - Experience implementing SBOM generation, Sigstore/cosign signing, OpenTelemetry, or enterprise observability platforms. - Experience supporting AI-assisted software development or enterprise coding agent platforms. - Cloud, security, or DevSecOps certifications. ### Mindset Traits - You enjoy solving complex platform and governance challenges through thoughtful automation. - You balance engineering velocity with operational discipline and regulatory requirements. - You communicate effectively across engineering, security, operations, and executive stakeholders. - You think in systems and build solutions that scale beyond a single project. - You enjoy mentoring others and creating reusable capabilities that elevate entire engineering organizations. - You're curious about the future of AI-enabled software development and excited to shape how modern engineering teams work. ### Why join RAVL? - Work alongside experienced consultants solving meaningful, enterprise-scale challenges. - Help define how AI transforms software engineering and platform delivery within highly regulated industries. - Flexible, client-aligned hybrid work model—autonomy with accountability, adapting to client delivery needs. - Variable bonus & RRSP contributions tied to performance and delivery impact. - 4 weeks paid time off (plus public holidays). - Paid professional development days and continuous learning opportunities. - Comprehensive health & dental coverage, including mental health support. - Commitment to lifelong learning through mentorship, certifications, and continuous improvement.