Job Summary RadarFirst is seeking a Lead Platform Engineer, AI & DevSecOps Engineer to lead the next stage of our cloud, security, reliability, and AI operations maturity. This role will own the platforms, practices, and operating model that enable our engineering teams to build, deploy, monitor, secure, and continuously improve production SaaS systems and agentic AI capabilities.
Since launching RadarFirst's first agentic AI offering using AWS Bedrock, Amazon Bedrock AgentCore, and AgentCore Gateway, we are expanding the DevOps remit to include production-grade AI infrastructure and operations. The person in this role will help mature the environment required by customers in highly regulated industries, including governance, secure agent/tool access, observability, continuous LLM and agent evaluations, traceability, incident response, cost controls, and operational readiness for future agent development.
This is a hands-on technical leadership role. The right candidate is an experienced platform, DevSecOps, or SRE leader who can set direction, build shared engineering practices, mentor others, and create a more DevOps-forward engineering culture across historically siloed teams.
This position can be based out of our HQ in Portland, OR, or remote from anywhere in the U.S.
Our Technical StackOur front end is built with Angular and Material Design, using TypeScript for strong typing and maintainability. Backend services are written in Go and Nest.js.
Technologies currently in use include Packer, Ansible, Docker, Terraform, CloudFormation, Python, Go, Bash, Datadog, Git, TeamCity, Jira, Slack, and Google's productivity suite.
We deploy on AWS using EC2, ECS, RDS-hosted PostgreSQL, S3, OpenSearch, Lambda, SES, CloudWatch, IAM, and related AWS services. Our agentic AI environment uses AWS Bedrock, Amazon Bedrock AgentCore, and AgentCore Gateway, with a growing need for AI-specific observability, evaluation, governance, and operational automation.
Essential Responsibilities & DutiesPlatform and Reliability- 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.
AI Operations- 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.
Security and Governance- 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.
Leadership and Culture- 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. Opportunity exists for people management for a small team.
Qualifications- 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.
Strong Plus- 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.
Research shows that people who identify as being from underrepresented groups are more likely to doubt the strength of their qualifications, so we encourage you to submit an application if you're interested in this role despite any reservations you may have about your background or skill set.
The salary range for this role is $155,000 - $175,000
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