Platform Engineering (Remote)

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Precisely is the leader in data integrity. We empower businesses to make more confident decisions based on trusted data through a unique combination of software, data enrichment products and strategic services. For starters, it means joining a company focused on delivering outstanding innovation and support that helps customers increase revenue, lower costs and reduce risk. We are committed to career development for our employees and offer opportunities for growth, learning and building community. With a "work from anywhere" culture, we celebrate diversity in a distributed environment with a presence in 30 countries as well as 20 offices in over 5 continents. Precisely is an AI-first organization. All employees are expected to demonstrate proficiency in applying AI tools to accelerate their work, improve output quality, and eliminate low-value tasks. Candidates should be comfortable using generative AI tools (e.g., Microsoft Copilot, ChatGPT) in their day-to-day workflows, able to evaluate AI-generated outputs critically, and open to continuously adopting new AI capabilities as they emerge.

This position is 100% remote anywhere in the US

We are hiring a Platform Engineer to lead security tooling and enablement within Platform Engineering for our global SaaS environment. This role focuses on building the platforms, automation, and guardrails that help engineering teams adopt security requirements in practical, scalable ways across the software development lifecycle.

You will work at the intersection of Security, Platform Engineering, and development teams. In our model, the Security team defines policies, standards, and best practices, and Platform Engineering enables and enforces them through engineering solutions. This is an individual contributor role for an engineer who can lead proofs of concept, help drive initiatives, and turn complex problems into clear, executable solutions.

Lead security tooling across application security, dependency and supply chain security, artifact and container security, cloud security posture, and policy-driven workflows

Build, integrate, and operate tools such as GitHub Advanced Security, JFrog Xray, Prisma, Black Duck, Checkmarx, and similar platforms

Design automation for vulnerability detection, dependency hygiene, patch planning, remediation tracking, and governed security workflows

Partner with Security and Engineering to turn defined policies and best practices into practical controls, delivery pipeline guardrails, and developer-friendly workflows

Improve the developer experience of security tooling by reducing noise, improving remediation clarity, and helping teams move faster without weakening security controls

Support the ongoing health and improvement of security tooling, including internally built or AI-assisted security automation where appropriate

Work with operational teams to support secure adoption of AI-enabled engineering tools and build controls around their use where needed

2+ years of experience in security engineering, platform engineering, development operations, site reliability engineering, or software engineering in production environments

Strong programming or scripting skills in Go, Python, Bash, or similar languages

Hands-on experience with security tooling and practices across areas such as code scanning, dynamic testing, software composition analysis, secret scanning, container or image scanning, artifact security, cloud security posture management, and policy enforcement

Experience with or exposure to tools such as GitHub Advanced Security, JFrog Xray, Prisma, Black Duck, Checkmarx, Dependabot, Renovate, or similar security and dependency management platforms

Strong understanding of vulnerability management, dependency management, and security controls within software delivery and developer workflows

Familiarity with Kubernetes, containers, cloud platforms, Git-based workflows, and infrastructure as code concepts

Strong collaboration and communication skills, with the ability to translate security needs into practical engineering solutions

AI Skills/Knowledge:

Experience using AI-assisted tools to improve engineering productivity, security workflows, and developer experience

Familiarity with AI-assisted coding tools such as GitHub Copilot or Cursor for work such as code review, documentation, and test generation

Experience applying AI to security use cases such as log analysis, threat investigation, remediation support, or security documentation

Familiarity with large language model APIs, agent-based workflows, or internally built AI tooling, along with the ability to evaluate and enable these tools responsibly within engineering environments

Understanding of security considerations for AI tools, including data leakage, prompt injection, shadow AI, and compliance with enterprise AI policies

Experience supporting AI-assisted or internally built security automation

Familiarity with modern software delivery environments where security tooling must balance risk reduction with engineering velocity

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