AI Solutions Engineer - Internal Delivery (m/f/d), Saint-ouen

Die Allianz Gruppe gehört zu den größten und renommiertesten Finanzdienstleistern der Welt und bietet ein internationales Netzwerk bekannter Marken mit erstklassigen Produkten. Vor allem streben wir nach Spitzenleistungen in unserem Alltag - das heißt, in den Beziehungen zu unseren Kunden, unseren Aktionären, unseren Mitarbeitern und zur Gesellschaft. Die Allianz Gruppe ist für über 76 Millionen Kunden in rund 70 Ländern tätig.

Als verlässlicher Partner verwaltet Allianz Global Investors Vermögen in allen wesentlichen Anlage-klassen und -regionen. Unsere Experten sind in 19 Märkten weltweit vertreten, mit umfassender Prä-senz in Europa, den USA und in Asien. Mit rund 650 Anlagespezialisten deckt unser Investment-Ma-nagement alle wichtigen Finanz- und Wachstumsmärkte der Welt ab. Erstklassiger Service vor Ort sorgt dafür, dass die globale Expertise beim Kunden ankommt.

Tasks

• Embed & own delivery: Translate internal objectives into scoped workstreams, delivery plans, and acceptance criteria; hold the bar on KPIs/SLAs, cost, and timelines from first prototype to stable operations.
• Shape solution design: Select fit-for-purpose approaches (predictive ML, GenAI, agents, decisioning, automation), data sources, and integration patterns; define NFRs (security, privacy, performance, reliability, cost).
• Data integration & discovery: Inventory and profile data sources and target/output systems; assess and prototype source connections (APIs, event streams, DBs, files) and output integrations (apps, services, analytics/BI, operational systems).
• Build hands-on: Develop production features (APIs, orchestration, evaluators, prompts, simple UIs) and integrate with our internal platform (data/storage, compute, identity, networking, monitoring) to ship usable software—not just POCs.
• Launch & scale: Run pilots/A-B tests and phased rollouts with internal teams; drive change management, training, and enablement to achieve adoption and measurable uplift in business KPIs.
• Operate & improve: Establish monitoring, evaluations/guardrails, incident handling, and continuous improvement for quality, drift, safety, and cost; maintain runbooks, service/model cards, and playbooks.
• Governance by design: Embed GDPR, privacy-by-design, Responsible AI controls, and EU AI Act readiness with Risk, Legal, and Compliance from discovery through operations.
• Stakeholder engagement (internal-first): Communicate progress, risks, and trade-offs in business terms to product owners and leaders; coordinate with internal platform and data teams; remove delivery blockers.
• Troubleshoot end-to-end: Triage data, model, and integration issues across environments; drive rapid root-cause and remediation.

Profile

• 2 to 4 years delivering AI/analytics solutions in enterprise settings with end-to-end involvement from scoping to steady-state ops.
• Education: Bachelor’s/Master’s in CS, Data/AI, Statistics, or related—or equivalent practical experience delivering AI solutions.
• Engineering-first mindset: Proficiency writing production code (e.g., Python/TypeScript/SQL); comfortable standing up integrations, workflows, and lightweight UIs to meet internal user needs quickly.
• AI solution patterns: Working knowledge across predictive ML, GenAI/LLMs, and AI agents; experience with evaluation, guardrails, and reliability in production.
• Cloud & platform: Practical experience with Azure for enterprise deployment; bonus for containers/Kubernetes, CI/CD, and observability.
• ML/AI operations: Experimentation, deployment, monitoring, incident management, lifecycle controls, and cost/performance optimization.
• Internal stakeholder fluency: Ability to translate business needs into delivery plans; communicate complex topics clearly to non-technical stakeholders; thrive in ambiguous, cross-functional environments.
• Governance: Working knowledge of GDPR, EU/AI Act, Responsible AI, and control frameworks; experience partnering with Risk/Compliance.
• Tools: Effective use of AI-assisted dev tools (e.g., GitHub Copilot) to accelerate build and delivery.
• Languages: English (fluent).