AI Security & Governance Engineer
About Astound Digital
At Astound Digital, we are pioneers in the digital landscape, dedicated to transforming how the world interacts with technology, data, and creativity. Our role as trusted advisors in the digital landscape empowers the world’s most innovative brands with frictionless, end-to-end customer experiences. We are known for our comprehensive solutions, proven expertise, and collaborative, nimble approach that instills confidence in our clients. We embrace the power of Artificial Intelligence (AI) to drive innovation, efficiency, and better outcomes for our clients and employees. Join us to navigate and lead in the ever-changing digital world, where your impact will extend beyond the ordinary.
Job Purpose
At Astound Digital, we have identified, piloted, and implemented an internal AI platform that uses AI tooling across our client delivery to enable our teams to collaborate, develop, and manage, and drive project and internal work more effectively and efficiently . Over the past eighteen months, this work has produced a unified LLM access layer for our engineering organization with tiering and spend limits, a knowledge and tooling platform on GCP built around Vertex AI Search and MCP, and a growing set of client commitments regarding how data is handled inside AI systems. Most client delivery ships on Salesforce, with our Anthropic practice leveraging Claude on top of it. Currently, all of this relies on architectural decisions and manual oversight.
Astound Digital is looking for someone to own security and AI engineering end-to-end: turn existing practice into a managed function, address the technical risks in the AI platform, and position our AI security as a core asset in enterprise client conversations rather than a source of unexpected questions.
This is a greenfield role with no legacy constraints or ready-made processes. This is an opportunity to own, define, and refine security and AI engineering across the processes, platforms, and firm.
Key Responsibilities
AI platform security
- Threat modelling for RAG and agentic scenarios: indirect prompt injection through indexed content, trust boundaries between data sources, context isolation between client projects
- Reviewing and controlling MCP integration permissions: which tools agents can reach, who approves extending that perimeter, how changes get re-reviewed
- Designing and implementing guardrails and data-leakage controls across AI pipelines
- Security review of AI functionality before it ships to production
- Working with the platform team on logging and monitoring for AI services: what must be logged, which detections to build, what alerting looks like
- Reviewing connected app configuration and OAuth scopes for AI integrations into Salesforce orgs, ours and our clients'
- Client-facing AI delivery
Security review of the AI solutions we deliver to clients, on Salesforce (Agentforce, Data Cloud, MCP connectors into client orgs) and on the Anthropic platform (Claude API, Claude Enterprise, Claude Code, Claudeforce plugins), against an agreed turnaround so review is a gate and not a queue
- Owning the standard answers on how client data is handled across the platforms we deliver on: retention, residency, model routing, what the provider sees and what it keeps, so the practices and sales are not reconstructing them per deal
- Maintaining the inventory of client-facing AI deployments with the model provider, routing path and billing path recorded for each
- Scoping and managing the per-engagement red teaming we buy in, and folding findings back into the guardrail baseline
AI governance and risk
- Owning internal AI policy: model access tiers, acceptable use, the exceptions process, while coordinating with the respective organizations such as Legal and HR
- Defining the sanctioned path to each model provider, including direct API access where a partner program or client contract requires it, and keeping routing choices visible to the practices that depend on them
- Maintaining the inventory of AI systems and vendors, and reassessing risk on a regular cadence
- Mapping our practice to NIST AI RMF and ISO 42001, and maintaining evidence for SOC 2
- Reviewing AI clauses in contracts and DPAs alongside Legal, and taking part in due diligence on new AI vendors
- Answering the AI sections of client security questionnaires and joining pre-sales conversations when the discussion turns to our AI practices
Operational control
- Managing access and spend limits across AI development tooling, including BYOK configurations and SDK surfaces that bypass ordinary monitoring
- Finding shadow AI: unapproved services, personal accounts, work routed around the sanctioned path
- Enabling engineers internally, framed as how to use AI tools safely rather than as a list of prohibitions
Qualifications and Skills
- 4+ years in information security: application security, cloud security, infrastructure security or security engineering
- Hands-on experience with a public cloud
- A working understanding of how LLM applications are put together: system prompts, RAG pipelines, tool calling, agentic patterns. Not from reading about it, but from having taken a real architecture apart and reasoned about how to break it
- Familiarity with the OWASP Top 10 for LLM Applications
- Experience with at least one compliance framework (ISO 27001, ISO 42001, SOC 2, NIST) and a clear sense of what separates real evidence from paperwork
- The ability to explain technical risk to a non-technical audience. A significant part of this role is conversations with Practice Leads, leadership and clients
- Working knowledge of Salesforce platform security as it applies to AI: Agentforce and the Einstein Trust Layer, connected apps and OAuth scopes, Data Cloud data handling. Most of our client AI work ships on Salesforce
Nice to have
- GCP experience, particularly Vertex AI
- Experience administering AI development tooling at organisation scale: Cursor, Claude Code or equivalent, managing access, model tiers and spend limits
- Familiarity with the Anthropic ecosystem: Claude Enterprise administration and retention controls, Claude API and Claude Code enterprise controls, MCP server permission models, security patterns for agentic workflows
- Practical adversarial testing of LLMs: garak, PyRIT, promptfoo, Giskard or similar
- Familiarity with MITRE ATLAS
- Familiarity with EU AI Act requirements
- Experience with threat modelling and design-level security review
- Experience with IAM, privileged access and audit logging in cloud environments
- Experience in a services or agency model, where security is discussed directly with the client
- Python scripting for automating controls and reporting
- Public work: contributions to open security tooling, bug bounty write-ups, talks
- Salesforce and Claude together: Agentforce with Claude as the model, Claudeforce plugins, Salesforce MCP connectors
- Experience answering sector security questionnaires in financial services, insurance or healthcare: GLBA, HIPAA, PCI DSS
What we offer in return
- Global Collaboration: The opportunity to work daily with diverse and talented professionals across the globe.
- Off-the-Charts Career Growth: Сlear career path and a performance review system, career coaching, training and certifications, mentoring and knowledge sharing.
- Well-being Is Top Priority: Parental leave, paid time off, comprehensive health and medical plans.
- Real Work-Life Balance: Dependent on location, we offer remote, in-office, or hybrid working modes; flexible hours; work-life balance support on every stage and level.
Why work for Astound Digital?
Whether you’re working directly with our world-renowned clients or with your Astound colleagues from around the globe, you will shape the future of digital commerce, using emerging technologies and innovative approaches.
Grow your career with Astound Digital, and discover exciting opportunities while doing the work you love!