Lead AI Transformation Engineer

Description

Accelerate Your Career in Cybersecurity!

Pentera is the market leader in AI-native Security Validation, equipping enterprises with the platform to proactively test their defenses against the latest cyber attacks. Pentera proves which exposures are truly exploitable across the entire attack surface and drives remediation workflows that reduce real risk. Anchored in real-attack validation, the Pentera platform powers the full Continuous Threat Exposure Management (CTEM) cycle, from exposure discovery through prioritization, validation, and mobilization. Thousands of security teams around the world trust Pentera to close their security gaps before threat actors can exploit them.

With over 350 team members and 1,300 customers in more than 60 countries, Pentera is a growing company supported by top investors such as Insight Partners, K1, and The Blackstone Group.

If you want to grow your skills, make an impact, and be part of an innovative team, Pentera is the place for you.

About the role

Pentera, a security company, is building an internal AI capability across the organization: agents that perform real tasks as the organization, with ROI and security assessed at every step. We are looking for a senior engineer who owns this end to end - a hands-on builder who also carries the senior function: setting the technical strategy, making the architecture calls, and being the person leadership trusts on internal AI.

This is not a pure IC build role and not a pure strategy role. You will personally build the flagship systems - production agents, the context layer, the evaluation and safety stack - while also deciding what gets built, in what order, and to what standard. You will work across R&D, IT, Security, BizOps, Customer, Sales, Marketing, People, and Finance, with the AI Transformation Officer owning the business portfolio.

What you'll do - strategy and senior function

- Own the technical strategy for Pentera's internal AI transformation: target architecture, model and vendor choices, build-vs-buy calls.
- Shape the AI portfolio: which workflows to automate, in what sequence, with what success metrics - and push back when the wrong thing is being built.
- Set and enforce the bar on ROI and security for every AI system: cost, adoption, cycle-time impact, access control, and auditability are reviewed per project, not after launch.
- Act as the senior technical voice for internal AI: advise leadership, review AI initiatives across the org.
- Turn one-off builds into a real internal platform: reusable patterns, shared services, and standards that AI Champions and teams adopt.
- Mentor AI Champions; raise the org's practical AI level.
- Manage Pentera's AI- Champions Community.
- Continuously evaluate models, vendors, and frameworks, and keep Pentera agile.

What you'll do - hands-on build

- Personally design, build, deploy, and own the flagship internal agents and AI workflows, from prototype through production.
- Build and evolve Pentera's AI context layer: connectors, APIs, retrieval services, metadata, identity and authorization, controls, and tool interfaces.
- Create safe action tools for agents and infrastructure for agents to work.
- Build RAG, tool-calling, structured-output, and multi-step agentic workflows using the right model and architecture for each problem.
- Own the production quality bar for what you ship: evaluation datasets and automated checks (accuracy, groundedness, task completion, safety, cost etc.)
- Work directly with business owners to map processes, test with users, and drive each pilot to a clear scale-or-stop decision.
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REQUIREMENTS

- 4+ years of production software engineering, including strong Python, APIs, testing, CI/CD, data contracts, and cloud services. Applied and agentic AI is a new field - nobody has a decade of it - so we weight demonstrated ownership and depth over years: what you shipped, what you owned end to end, how deep you went.
- Evidence of operating at senior scope, wherever you earned it: you have set technical direction, made architecture calls that others built on, and carried systems end to end - as a staff/lead engineer, a first AI hire, or similar.
- Executive fluency: you turn ambiguous business needs into a technical plan, explain trade-offs simply to non-engineers, and say no with reasoning when needed.
- Ownership mindset: you measure whether the system changed the business process, not whether the demo ran.

Advantages

- Experience as a first or early AI hire, or standing up an internal AI platform or function.
- Product management experience.
- Experience building internal platforms or company-wide data products.

We are an equal opportunity employer and we are committed to building a diverse and talented workforce. We do not discriminate on the basis of race, sex, religion, colour, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, medical condition, disability, or any other class or characteristic protected by applicable law. We welcome candidates from all backgrounds to join us!