Tooling Platform Engineer – Harness

Job Description

1. Software Delivery Platform Ownership Harness

• Own the Harness platform as the clients 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: 612 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 Java Go or .

• Experience with GitHub or Atlassian toolchains.