AI
Aleph Group, IncTechnical Product Manager
Technical Product Manager at Aleph shaping product strategy for ad platforms. Collaborate with teams to enhance operational efficiency and user experience for critical internal systems.
About the role
- Take ownership of core Enterprise IT AI capabilities: connectors, LLM services, knowledge ingestion, guardrails, governance tooling.
- Partner closely with central AI Function, Infrastructure, End-User Support, Security, Legal, Privacy, and other IT teams.
- Define, deliver, and continuously improve technical products, integrations, and operating model enabling AI at scale.
- Own product vision, roadmap, and backlog; translate business needs into PRDs, epics, and acceptance criteria.
- Balance quality, cost, and latency trade-offs for AI workloads and align backend capabilities with agent experiences.
- Scope, design, and deliver secure AI connectors for enterprise platforms and partner on performance, resiliency, disaster recovery.
- Lead document classification, taxonomy initiatives, and define ingestion, enrichment, and retention standards for enterprise knowledge.
- Establish data access rules, redaction/DLP policies, and least-privilege models to protect PII and sensitive content.
- Define LLMOps quality metrics, run A/B experiments, and establish observability (feedback loops, drift detection, hallucination monitoring).
- Partner on policy, DPIAs, data residency, logging, audit, and define incident response runbooks; coordinate with Problem/Change Management.
- Establish RACI across AI, Enterprise IT, and business units; build enablement for End-User Support and coordinate training and adoption programs.
- Own OKRs and executive reporting for EIT AI; continuously re-prioritize based on business impact, risk, and feedback.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (Master’s is a plus).
- Minimum of 3 years delivering AI/ML or data-driven products in enterprise environments.
- Proven track record rolling out transformational capabilities at global scale (multi-region, multi-tenant, regulated environments).
- Hands-on familiarity with LLMs and AI platforms (OpenAI, Anthropic, Gemini, Azure OpenAI, AWS Bedrock); exposure to Google Agentspace preferred.
- Practical experience with RAG architectures, embeddings, prompt management, evaluation frameworks, and guardrails.
- Practical experience building secure connectors and APIs (REST/GraphQL), eventing, and middleware patterns.
- Experience with cloud platforms (GCP, Azure, AWS), identity and access (Azure AD/Entra, Okta), and secrets management.
- Experience with Enterprise IT platforms such as Microsoft 365/SharePoint, Jira/Confluence, Slack.
- Strong grounding in security, privacy, and compliance for AI (DLP, PII handling, retention, audit).
- Comfortable with Agile/Scrum; able to write crisp PRDs and sequence/architecture diagrams.
- Excellent communication and stakeholder skills, with the ability to influence, drive alignment, and lead change across technical and non-technical teams.
- Nice to have: ITIL v4 and cloud certifications (GCP, Azure, AWS).
- Corporate language English; submit application in English.
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