Lead Platform Engineer, AI and DevSecOps

RadarFirst is hiring a Lead Platform Engineer to lead its cloud, security, reliability, and AI operations maturity. The role owns platform and DevSecOps strategy, operates secure AWS and AI infrastructure, and advances governance, observability, incident response, and engineering practices for production SaaS and agentic AI systems.

Responsibilities:

• Own and evolve the DevSecOps, platform engineering, and AI operations roadmap, with clear goals for reliability, security, deployment maturity, developer productivity, auditability, and customer readiness
• Design, implement, and operate secure, scalable, fault-tolerant AWS infrastructure for SaaS and AI workloads
• Implement automation to reduce manual deployment, provisioning, compliance, monitoring, and support work
• Monitor platform KPIs and cost drivers, including cloud spend, token consumption, model usage, latency, error rates, deployment frequency, change failure rate, recovery time, and operational toil
• Lead the operational maturity of RadarFirst's agentic AI platform, including the management of AWS Bedrock, AgentCore, AgentCore Gateway, agent/tool governance, policy controls, observability, evaluation workflows, and cost management
• Build observability across infrastructure, applications, and agentic workflows, including logs, metrics, traces, token usage, latency, error rates, tool invocation behavior, evaluation results, and customer-impacting SLOs
• Partner with Engineering, Product, Security, Compliance, and Customer-facing teams to ensure AI systems meet expectations for regulated industries, including auditability, access control, privacy, traceability, incident response, and defensible governance
• Define and evolve CI/CD, infrastructure-as-code, and release-management practices that improve speed, safety, reproducibility, and rollback confidence
• Lead incident response and reliability improvement efforts, including post-incident reviews, root-cause analysis, alert tuning, runbooks, operational readiness reviews, and long-term remediation
• Maintain and improve security practices across cloud infrastructure, CI/CD, secrets management, authentication, authorization, vulnerability scanning, and software supply chain controls
• Create shared engineering standards and paved paths that help product engineers ship safely without waiting on bespoke DevOps support
• Drive a DevOps-forward engineering culture by reducing team silos, improving ownership models, clarifying operational responsibilities, and coaching teams on secure, observable, supportable software delivery
• Mentor DevOps, platform, and software engineers; help develop future technical leaders and raise the organization's operational bar

Requirements:

• 10+ years of experience in DevOps, DevSecOps, SRE, platform engineering, cloud infrastructure, or a closely related engineering role
• Proven track record designing and operating production AWS infrastructure for SaaS or enterprise software environments
• Experience leading technical strategy, mentoring engineers, influencing cross-functional teams, and improving engineering culture
• Strong hands-on experience with infrastructure as code, CI/CD, containerization, configuration management, scripting, and operational automation
• Experience with AWS services such as EC2, ECS, IAM, RDS, S3, Lambda, CloudWatch, OpenSearch, and related networking and security services
• Practical understanding of secure SDLC, application security, privacy, compliance, auditability, and risk management in regulated customer environments
• Experience with observability platforms and practices, including metrics, logs, traces, SLOs, alerting, dashboards, and incident response
• Familiarity with AI infrastructure, LLMOps, AgentOps, or MLOps concepts, especially production monitoring, evaluations, governance, cost optimization, and safe release practices for non-deterministic systems
• Strong understanding of secrets management, certificates, authentication, authorization, encryption, and cloud security controls
• Experience with vulnerability management and security tooling such as SCA, SAST, DAST, IAST, RASP, penetration testing, and security monitoring
• Excellent communication, collaboration, leadership, analytical, and troubleshooting skills
• Hands-on experience with AWS Bedrock, Amazon Bedrock AgentCore, AgentCore Gateway, or comparable agentic AI platforms
• Experience implementing LLM or agent evaluation frameworks, including automated regression tests, golden datasets, human review workflows, prompt/version management, safety checks, and release thresholds
• Experience building governance for agent tool access, including policy enforcement, identity, permissions, audit trails, redaction, approval flows, and controlled access to internal systems
• Experience with OpenTelemetry, CloudWatch, Datadog, Langfuse, Arize/Phoenix, Promptfoo, TruLens, OpenAI Evals, or similar AI observability/evaluation tools
• Experience with regulated customers in healthcare, insurance, financial services, government, or privacy/security-sensitive industries
• SaaS scale-up experience
• Certifications or training such as SANS/SEC-540, SSCP, CISSP, CAP, CSSLP, HCISPP, AWS Certified DevOps Engineer, AWS Certified Security Specialty, or AWS Certified Machine Learning Specialty