Build and operate a financial cloud developer platform supporting independently versioned modules across global compliance sites. Responsibilities include CI/CD pipelines, reproducible builds, supply chain provenance, dependency graph and change impact tooling, GitOps deployment automation, Kubernetes controllers, site provisioning, version management, security patching, and test orchestration.
APN Job ID# 175546
About the Role
You will be a core builder of the Financial Cloud developer platform — implementing the CI/CD pipelines, GitOps automation, artifact management, dependency graph engine, and change impact analysis tooling that allow 50–100 versioned modules to be independently built, tested, composed, and deployed across dozens of global compliance sites.
Key Responsibilities
- Build module-level CI/CD pipelines: commit to versioned artifact (Docker image + K8s manifest) with hermetic builds, pinned toolchains, and deterministic outputs
- Implement build provenance automation: SLSA attestation, artifact signing, dependency chain verification, Golden Signals validation in CI
- Develop the dependency graph database: ingest static + runtime dependencies, provide a queryable graph for change impact analysis
- Build change impact analysis tools: PR-level affected module/site/test computation surfaced in PR review UI; selective test orchestration
- Implement GitOps deployment engine: ArgoCD/Flux controllers, staging-canary-production promotion with Golden Signals monitoring and auto-rollback
- Build site provisioning tooling, version management console, security patch force-push pipeline, and four-layer test orchestrator
Major Requirements
- 6+ years in backend / platform / infrastructure / developer tools engineering
- Strong proficiency in Go (primary) or Java/Kotlin, with Python scripting
- Production CI/CD pipeline development: GitHub Actions, Tekton, Jenkins, or custom orchestrators
- GitOps at scale (10+ clusters): ArgoCD, Flux, Kustomize
- Kubernetes: operators, custom controllers, CRDs, Helm chart development
- Build systems: Bazel or Gradle — reproducible builds, remote caching, build graph optimization
Preferred / Bonus
- Experience with dependency analysis tooling or graph databases (Neo4j, Dgraph)
- Supply chain security: Sigstore, in-toto, SBOM generation
- AWS (CodePipeline, CodeBuild, Proton) or GCP (Cloud Build, Artifact Registry, Cloud Deploy)
Compensation
Base salary: USD 200,000–300,000 per year (negotiable).
About IntelliPro
IntelliPro Group Inc. is a global staffing and talent solutions company. We connect exceptional professionals with leading organizations across technology, engineering, and professional services. By partnering closely with both clients and candidates, we build long-term relationships that help businesses grow and careers thrive.
IntelliPro Group Inc. Santa Clara, California, USA Office
3120 Scott Blvd, Ste 301, Santa Clara, CA, United States, 95054
IntelliPro Group Inc. Mountain View, California, USA Office
Mountain View, United States
Similar Jobs
eCommerce • Fashion • Retail • Sales • Wearables • Design
Assist customers with product selection and styling, provide knowledgeable recommendations, create complete looks, support purchase decisions, and deliver a seamless checkout experience. Drive sales through customer engagement and brand storytelling while maintaining product knowledge, stockroom organization, POS accuracy, and operational excellence. Requires flexible availability, teamwork, physical ability to handle merchandise, and willingness to learn omni-channel selling techniques.
Top Skills:
Pos
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Leads engineers and data scientists developing autonomy subsystem evaluation metrics, root-cause analyses, regression detection, and release decision tools. Owns roadmap, staffing, technical quality, and cross-functional alignment across planning, perception, prediction, and localization. Applies statistical evaluation, simulation and road data analysis, and VLMs/LLMs to determine how subsystem errors affect driving outcomes and communicate actionable findings to engineering and leadership.
Top Skills:
C++LlmsPythonSQLVlms
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Leads four teams responsible for evaluating autonomous-driving performance, classifying scenarios, analyzing subsystem failures, and translating results into engineering and release decisions. Owns roadmap, staffing, technical quality, metrics, statistical rigor, and stakeholder trust. Hires and develops managers, engineers, and data scientists while guiding evaluation strategy, regression detection, simulation and road-test analysis, and AI-assisted classification initiatives using VLMs and LLMs.
Top Skills:
Autonomous Driving SystemsLlmsMachine LearningPythonSimulationSQLVlms
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
