# Lead Platform Engineer, AI and DevSecOps at RadarFirst

> Remote · United States · Staff · Backend · open. Source: https://alderhq.app/jobs/greenhouse%3Aradarfirst%3A5451311008 (read 2026-11-10).

## Facts (observed)

- Company: [RadarFirst](https://alderhq.app/companies/radarfirst)
- Location text: United States, Remote; United States
- Where it can be done from (inferred): Remote · United States (evidence: "Remote role open worldwide")
- Posted: 2026-10-13 (28 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://www.radarfirst.com/careers/?gh_jid=5451311008
- Skills listed (inferred): TypeScript, JavaScript, Angular, NestJS, Python, Go, PostgreSQL, Elasticsearch, AWS, Docker, Terraform, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (United States, n 187): p25 $215k, median $239k, p75 $260k

## Description (the employer's text)

### 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 Stack

Our 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 & Duties

### Platform 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.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aradarfirst%3A5451311008 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.