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Lead Platform Engineer

Exiger - McLean, VA, United States - Hybrid - posted 2026-10-21

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Exiger is an AI-native platform for supply chain and procurement automation, serving 550+ global customers including 150 Fortune 500 companies and 80+ government and defense organizations. The company is FedRAMP authorized and a 2x Gartner Magic Quadrant Leader for Supplier Risk Management. You will be the technical lead for Exiger's largest, most cross-cutting platform programs spanning multiple engineering teams with significant security, compliance, and reliability implications across commercial AWS and FedRAMP-authorized AWS GovCloud environments. This is a senior individual contributor role with no direct reports; your impact comes through technical judgment, clear communication, and the trust of peer teams. Key responsibilities include: - Lead large cross-team platform initiatives (multi-region EKS, GovCloud expansion, IaC framework re-architecture) from design through delivery - Own architecture decisions across compute, networking, identity, account structure, and delivery; document tradeoffs clearly - Reduce system complexity by consolidating patterns, retiring obsolete approaches, and enabling teams to do more with less - Design enterprise IaC frameworks and multi-region CI/CD pipelines with approval gates, automated rollback, and policy enforcement - Architect guardrails and developer tooling for safe FedRAMP and GovCloud operations - Design and validate disaster recovery, capacity, and resilience strategies with explicit RTO/RPO targets using load testing, failure injection, and chaos testing - Partner with product, data, and AI/ML teams to design platform infrastructure aligned with their operational needs - Communicate plans, risks, and tradeoffs to engineers, security, compliance, federal program teams, and business stakeholders; surface risks early and manage dependencies - Own on-call escalation, lead critical incidents, and drive incident response improvements across served teams - Set platform best practices and quality standards (IaC testing, policy tests, failure testing in CI) that other teams adopt - Guide adoption of AI-assisted engineering tools with clear validation standards respecting federal compliance - Mentor and coach engineers across teams, delegate meaningful work, and raise hiring standards for platform roles Requirements: - Track record as technical lead on large, cross-team infrastructure or platform programs with many stakeholders - Advanced, production-proven expertise in AWS, Terraform, Kubernetes/EKS, and CI/CD, including architecture decisions with lasting impact - Excellent judgment on multi-faceted architecture with documented reasoning and rejected alternatives - Concrete examples of reducing system or process complexity with measurable outcomes - Experience translating FedRAMP, NIST 800-53, and SOC 2 requirements into automated, enforceable controls with continuous evidence - Excellent written and verbal communication: design proposals, decision records, incident reviews; ability to explain tradeoffs to engineers, auditors, and business leaders - Evidence of growing engineers through mentoring, coaching, and delegation - Strong Python or Go skills for platform tooling and automation - Typically 10+ years of engineering experience, including 3+ years as technical lead on cross-team programs (calibrated on demonstrated scope and judgment, not tenure) - U.S. citizenship required for access to FedRAMP federal environments Nice to have: - Leadership or central role in FedRAMP authorization, continuous monitoring, or SOC 2 Type II audit - AWS GovCloud experience including partition isolation and service parity constraints - AWS Professional/Specialty, CKA/CKS, or HashiCorp Terraform certifications - Internal developer platforms or portals (Backstage or equivalent) - Service mesh (Istio, Linkerd) and container supply chain security - HashiCorp Vault at scale - Chaos engineering (AWS Fault Injection Service, Chaos Mesh, Litmus) - FinOps and automated cost controls - Infrastructure for data and AI/ML workloads (GPU scheduling on EKS, Amazon Bedrock, SageMaker)

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