Tooling / Platform Engineer – Harness

Job Description

1. Software Delivery Platform Ownership – Harness

• Own the Harness platform as the client’s enterprise delivery platform, including architecture, configuration standards, RBAC, governance model, module adoption roadmap, and vendor relationship.

• CI (Continuous Integration): Establish reusable pipeline templates, shared libraries, build caching, parallelization standards, and CI patterns to maintain build times within target as the organization scales.

• CD (Continuous Delivery): Define deployment strategies, including progressive delivery, canary, and blue-green deployments; GitOps workflows; environment and artifact promotion paths; approval gates; and change-control evidence for regulated payment workloads.

• STO (Security Testing Orchestration): Integrate SAST, DAST, SCA, container, and secrets scanning across pipelines. Collaborate with AppSec to define severity thresholds, blocking versus advisory policies, exemption workflows, and remediation SLAs.

• SEI (Software Engineering Insights): Define engineering metrics, including DORA, flow, lead time, and review latency. Establish appropriate guardrails to ensure metrics identify system-level constraints rather than evaluate individual engineers.

• CCM (Cloud Cost Management): Implement cloud cost visibility, budgets, anomaly detection, non-production autostopping, and showback or chargeback models. Connect architecture decisions to unit economics and cost optimization.

• Establish policy-as-code standards to ensure pipeline governance is versioned, reviewable, and auditable rather than manually configured through a UI.

2. SDLC Toolchain Ownership

• Own the software delivery toolchain, including source control, issue tracking, artifact management, static analysis, and test infrastructure.

• Manage integration architecture, entitlements, license management, upgrade and migration planning, and consolidation of redundant tools.

• Define and maintain golden paths: documented, supported, and standardized workflows that enable teams to move from code commit to production, with deviations treated as explicit decisions.

3. AI in the Engineering Workflow

• Establish guidelines for using AI tools in software design, code generation, testing, and documentation.

• Define controls for safe AI adoption, including evaluation criteria, human review requirements, context and data-handling standards, and governance for AI-generated code entering production.

  Location: Atlanta, GA (Day 1 Onsite)
  Duration: 6–12+ Months Contract

  Engagement Type: Contract
  Work Arrangement: Onsite from Day 1

Required Qualifications

• 10+ years of experience in software engineering, solution architecture, or platform engineering, including senior architecture leadership for distributed, high-availability systems.

• Experience in payments, fintech, merchant services, or a comparably regulated transaction-processing domain.

• Proven ownership of an enterprise CI/CD platform, beyond simply using one.

• Strong experience with pipeline-as-code, templating and reuse at scale, RBAC design, secrets management, and multi-team governance.

• Experience with Harness, GitLab, Azure DevOps, GitHub Actions with Argo or Spinnaker, or Jenkins operated at scale.

• Experience integrating security scanning into delivery pipelines and establishing policy gates that engineering teams can effectively adopt.

• Working knowledge of engineering delivery metrics, including DORA or equivalent, their limitations, and potential misuse.

• Strong expertise in API and integration architecture, including REST, asynchronous messaging, event-driven patterns, and API lifecycle governance.

• Experience with cloud-native architecture and Kubernetes in production environments.

• Demonstrated ability to influence technical direction across teams without direct reporting authority and communicate technical trade-offs to executive stakeholders.

Preferred Qualifications

• Hands-on experience with multiple Harness modules, particularly STO, SEI, or CCM.

• Experience with policy-as-code frameworks such as OPA/Rego or equivalent.

• Experience owning cloud cost management or FinOps practices, including showback or chargeback implementation.

• Experience applying generative AI or agentic development patterns to real engineering workflows, including governance.

• Architecture leadership for large-scale API ecosystems, partner platforms, or merchant-facing onboarding.

• Experience with PCI DSS-aligned controls, IAM, or fraud/risk integration.

• Hands-on development experience with .NET, Java, Go, or Node.js.

• Experience with GitHub or Atlassian toolchains.