Full Stack Engineering Manager – Privacy, Security, AI Governance

Posted Sep 25

This is a fully remote position, open to applicants in United States.

📋 Description

• Transform client objectives, risk factors, and policy requirements into solution architectures, product specifications, engineering backlogs, and implementation strategies.

• Oversee the design, development, integration, testing, deployment, and troubleshooting of production applications and services.

• Create APIs, automated workflows, integrations, dashboards, and ancillary components.

• Embed governance into development and deployment through automated checks, controls-as-code, policy enforcement, and continuous monitoring.

• Construct prototypes, test methodologies, refine solution paths, and assist with proofs of concept, technical demonstrations, effort estimations, and pricing inputs.

• Manage delivery scope, timelines, quality, financial engagement, and client satisfaction.

• Address implementation challenges across applications, integrations, data, and deployment processes.

• Lead multidisciplinary delivery teams and provide mentorship to engineers.

• Create reusable tools, documentation, knowledge-sharing practices, and engineering standards.

• Provide solutions that tackle privacy, online safety, AI governance, sensitive data protection, data discovery, classification, DLP, encryption, PKI, and cryptographic capabilities.


⛳️ Requirements

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

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

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

• A minimum of 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 in designing or deploying generative AI or large language model (LLM) solutions in a client or production context.

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

• Proven experience leading technical workstreams, multidisciplinary teams, or engineering delivery teams.

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

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

• Willingness to travel approximately 25–50%.

• Limited immigration sponsorship may be available.

• Preferred: Proficiency in JavaScript or TypeScript and frameworks like React or Next.js.

• Preferred: Expertise in technical controls for generative AI, LLM, or agentic AI applications.

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

• Preferred: Experience in regulated environments involving SOX, PCI DSS, FFIEC, HIPAA, or GDPR.

• Preferred: Familiarity with Kubernetes, GitOps, Elasticsearch, OpenSearch, Neo4j, PyTorch, or TensorFlow.

• Preferred: Experience with product roadmaps, technical backlogs, or reusable engineering assets.

• Preferred: Senior engagement with client stakeholders for architecture and risk decisions.


🏝️ Benefits

• Remote work arrangement.

• Limited immigration sponsorship may be available.

• Opportunity to engage in projects focused on privacy, security, online safety, AI governance, and sensitive data protection.

• Mentoring and knowledge-sharing opportunities.

• Experience in technical leadership and client delivery.

• Approximately 25–50% travel depending on client and project requirements.

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