• Use customer and employee feedback, alongside operational data and insights, to inform improvements to the HR experience, quality, and outcomes. • Align initiatives with departmental strategic objectives and provide expert judgement on risk, compliance, and scalability, ensuring statutory and employment-related regulatory requirements are embedded directly into automation and system design decisions. • Scope and deliver as the Directly Responsible Individual (DRI) multi-phase initiatives across process redesign, tooling, and change management from planning, prototype, launch and optimization. • Map operational processes, identify bottlenecks, and architect end-to-end automated workflows that increase speed, accuracy, and scalability. • Build and maintain data pipelines via native connectors or APIs across HRIS, case management, payroll, and other tools to ensure seamless data flow, event triggers and reporting. • Leverage low-code/no-code platforms (like Zapier, Make, Retool, n8n or similar) to prototype and deploy rapid automations. • Deploy and govern AI tools or agents (e.g., for document processing, query triage, policy guidance, data auditing) that enhance efficiency, compliance and user experience. • Design and Implement multi-agent patterns (e.g. maker/checker setups, routing to specialised agents) and governance policies (e.g. retries, fallbacks, guardrails), embedding appropriate human oversight in employment-related workflows to ensure compliant and responsible AI deployment. • Build and maintain automation observability and governance (e.g. tracing, logging, agent runs evaluation) including access controls and auditability suitable for HR data. • Develop and maintain fit-for-purpose operational data models to support reporting, audit, compliance and data integrity initiatives within HR Operations. • Build and iterate on HR Operations analytics dashboards and reports (e.g. data audits, performance metrics) using SQL and BI tools such as Tableau or Sigma. • Foster strong cross-functional collaboration and support effective change management, training, adoption and continuous improvement of AI & Automation driven solutions. • Serve as a technical lead for AI & Automation within the Ops departments, contributing to the evolution of best practices and ways of working. • Mentor and guide junior team members, supporting capability uplift and operational maturity across the department.

• Unterstützung unseres Teams beim Fundraising, insbesondere durch Investorenrecherche und Pflege unserer Investorendatenbank • Entwicklung und Implementierung von Automatisierungslösungen, z. B. zur Unterstützung beim Deal Sourcing oder in Due-Diligence-Prozessen • Mitwirkung bei der Optimierung datenbasierter Rechercheprozesse mithilfe moderner AI-Tools

• Your primary goal is to build AI-powered infrastructure that gives VC and PE clients a genuine edge — proprietary systems that extract signals, automate decisions, and compound in value over time. • Agentic AI Systems: Multi-step LLM workflows, RAG pipelines, and agent orchestration systems — owned from architecture to production. From quick experiments to full production deployments — you know when to move fast and validate, and when to engineer for scale. Real clients depend on these systems to make investment decisions. • Full-Stack AI Applications: Client-facing web applications with AI embedded throughout — Python/FastAPI backends, React frontends, integrated with LLM providers (OpenAI, Anthropic, Gemini). Claude Code or Cursor is your primary environment. AI-assisted coding is your default mode, not a shortcut you reach for occasionally. • Data Platform Engineering: Scalable pipelines and cloud infrastructure (AWS/GCP) that underpin AI features — vector databases, data ingestion layers, API integrations. The foundation that makes everything else work. • Technical Discovery & Client Engagement: You’ll translate business needs into AI-first technical proposals — in the room with CFOs, GPs, and operating partners. You know what’s possible and you can explain it to someone who doesn’t write Python. • AI Quality & Internal Standards: Guardrails, automated testing, and observability for AI systems. You’ll help define what ‘good’ looks like across every engagement — contributing to internal engineering standards that compound over time.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are looking for a Director, Strategic Alliances-AI Ecosystem to join our team. This role offers flexible location options including onsite or hybrid at our San Jose Office, or remote within the USA, reporting to the Senior Director, PM-AI Security & Strategic Initiatives in the PM - Security AI department. This role is business development focused. What you’ll do (Role Expectations) - Identify, engage, and cultivate strategic partnerships with AI ecosystem players and hyperscaler partners, owning the outreach pipeline from initial contact through executive-level meetings. - Develop and execute a partnership go-to-market strategy that aligns AI ecosystem integrations with Zscaler’s security platform roadmap and revenue objectives. - Serve as the technical bridge between partners and Zscaler product management, translating partner capabilities and integration requirements into actionable product collaboration opportunities. - Build and maintain a structured partner engagement framework, including joint roadmap planning, co-development agreements, and ongoing relationship management cadences. - Represent Zscaler’s AI security vision externally at industry events, partner forums, and ecosystem working groups to expand brand presence and attract new partnership opportunities. Qualifications - 5+ years in product management or business development (including BDM and strategic partnerships), with at least 3 years dedicated to AI/ML ecosystems or cloud security platforms. - Proven track record of identifying, negotiating, and closing strategic technology partnerships with hyperscalers (AWS, Azure, GCP) or major AI ecosystem players (Anthropic, OpenAI, Databricks, CoreWeave, etc). - Strong technical acumen in AI/ML architectures and integration patterns, with the ability to translate between partner product teams and internal product stakeholders. - Experience developing and executing partnership go-to-market strategy that drive measurable revenue impact and platform adoption. - Excellent executive communication and relationship management skills, with demonstrated ability to engage C-level and VP-level stakeholders at partner organizations. Requirements - Experience in cybersecurity or zero-trust architecture, particularly in how AI is applied to threat detection, data protection, or security operations. - Existing relationships within the AI ecosystem (e.g., model providers, inference platforms, AI infrastructure vendors) or major hyperscaler partner programs. - MBA or advanced technical degree, or equivalent experience building and scaling partnership programs at a high-growth enterprise SaaS company. Benefits - Various health plans. - Time off plans for vacation and sick time. - Parental leave options. - Retirement options. - Education reimbursement. - In-office perks, and more!