Full Stack Engineering Manager – Privacy, Security & AI Governance

This is a remote position.

Full Stack Engineering Manager – Privacy, Security & AI Governance

B5 Recruiting is seeking a hands-on Full Stack Engineering Manager for a client opportunity combining technical leadership, software engineering, and client delivery.

In this role, you will lead the development of production solutions that address privacy, online safety, AI governance, and sensitive data protection. You will translate business and regulatory requirements into technical designs and guide teams through implementation while remaining actively involved in engineering delivery.

The ideal candidate can bring clarity to evolving requirements, lead multidisciplinary teams, and work effectively with product, engineering, security, privacy, legal, and compliance stakeholders.

What You’ll Do

• Translate client goals, risk considerations, and policy requirements into solution architectures, product specifications, engineering backlogs, and implementation plans.
  

• Lead the design, development, integration, testing, deployment, and troubleshooting of production applications and services, including AI-enabled capabilities, technical safeguards, and data protection integrations.
  

• Build APIs, automated workflows, integrations, dashboards, and supporting components. Incorporate governance into development and deployment through automated checks, controls-as-code, policy enforcement, and ongoing monitoring.
  

• Work with clients and technical specialists to develop prototypes, test approaches, and refine solution direction. Support new opportunities through proofs of concept, technical demonstrations, effort estimates, and pricing inputs.
  

• Manage delivery scope, schedules, quality, engagement financials, and client satisfaction. Resolve implementation challenges across applications, integrations, data, and deployment processes.
  

• Lead multidisciplinary delivery teams, mentor engineers, and establish reusable tools, documentation, knowledge-sharing practices, and engineering standards.
  

What You Bring

• Ability to balance hands-on engineering with team leadership and client responsibilities.
  

• Clear communication across technical and business audiences.
  

• Strong attention to delivery quality, documentation, and detail.
  

• Ability to build trusted stakeholder relationships and guide technical decisions.
  

• Strong prioritization skills and the ability to manage multiple workstreams and deadlines.
  

• A practical approach to mentoring, problem-solving, and providing clear direction.
  

About the Team

You will work with a multidisciplinary engineering team helping organizations improve the security, privacy, and reliability of their digital products, platforms, and data practices. The team partners with product, engineering, security, privacy, data, risk, compliance, and business functions to turn strategy and policy into working solutions.

Projects may include:

• Developing platform safety capabilities that help identify and address harmful online activity.
  

• Integrating privacy and product compliance requirements into applications and development practices.
  

• Building governance and technical safeguards for generative and agentic AI.
  

• Protecting sensitive information across cloud platforms, collaboration tools, applications, and enterprise systems.
  

• Implementing data discovery, classification, data loss prevention (DLP), encryption, public key infrastructure (PKI), and related cryptographic capabilities.
  

• Creating reusable engineering tools and components that simplify implementation and ongoing operations.
  

The team values technical curiosity, sound engineering practices, practical problem-solving, and an understanding of client needs.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, Cybersecurity, or equivalent demonstrated experience.
  

• At least 7 years of experience translating client requirements into solution architectures using REST APIs, microservices, event-driven patterns, or serverless services.
  

• At least 7 years of experience developing and deploying production solutions with Python, Java, or Node.js.
  

• At least 2 years of experience delivering solutions on AWS, Microsoft Azure, or Google Cloud, including containers, CI/CD pipelines, and version control.
  

• At least 1 year of experience designing or deploying generative AI or large language model (LLM) solutions in a client or production setting, including implementation, governance, or operational management of generative or agentic AI.
  

• Experience in at least one relevant domain: digital trust, online protection, trust and safety, security, product compliance, privacy, AI governance, data protection, or cryptography.
  

• Experience leading technical workstreams, multidisciplinary teams, or engineering delivery teams.
  

• Experience managing scope, schedules, quality, risks, dependencies, and client communications.
  

• Experience coaching or mentoring professionals and contributing to solution proposals, estimates, prototypes, technical demonstrations, or business development efforts.
  

• Willingness to travel approximately 25–50%, depending on client and project needs.
  

• Limited immigration sponsorship may be available for this opportunity.
  

Preferred Qualifications

• Experience building applications or demonstrations with JavaScript or TypeScript and React or Next.js.
  

• Experience implementing technical controls for generative AI, LLM, or agentic AI applications.
  

• Familiarity with AI use-case inventories, risk classification, human oversight, tool access restrictions, prompt-injection protections, logging, monitoring, or controls-as-code.
  

• Experience in regulated environments such as financial services, healthcare, or the public sector, including work involving SOX, PCI DSS, FFIEC, HIPAA, or GDPR requirements.
  

• Experience with Kubernetes, GitOps, Elasticsearch, OpenSearch, Neo4j, PyTorch, or TensorFlow.
  

• Experience owning product roadmaps, technical backlogs, or reusable engineering assets.
  

• Experience working with senior client stakeholders to guide architecture decisions and evaluate risk.