SBS builds mission-critical banking software and, together with our sister company Axway, now forms the 74 Software group. Within our Digital Banking Business Unit, we are assembling a small, high-impact team to craft a new generative-AI product line.
Your first mission: design and deliver a retrieval-augmented-generation (RAG) platform that lets bankers compose and deploy their own AI agents—securely, compliantly, and at scale. You will be one of the founding AI engineers on this journey, shaping architecture, practices, and culture from day one.
Key Responsibilities
1. GenAI Architecture & Development
End-to-end design of RAG pipelines: document ingestion, chunking, embedding, vector search, prompt engineering, guards, and evaluation.
Integrate open-source and commercial LLMs (e.g., OpenAI, Gemini, Llama-3 etc.) via LangChain / LlamaIndex or custom frameworks.
Build reusable “agent primitives” so non-technical users can chain tools, memory, and policies into bespoke banking assistants.
2. Data & Domain Governance
Implement data-classification, masking, PII scrubbing, and hallucination mitigation aligned to EU banking regs (EBA, GDPR, DORA).
Collaborate with our Risk & Compliance team to embed explainability and audit trails in every response.
3. MLOps & Platform Engineering
Containerize and orchestrate AI micro-services on Kubernetes/OpenShift; automate CI/CD with GitLab.
Own model lifecycle: evaluation suites, continuous monitoring, rollback strategies, and cost optimisation.
4. Collaboration & Leadership
Mentor two junior engineers and evangelise best practices across the company.
Work closely with Product, UX, and Solution Architects to translate banking workflows into agent capabilities.
Les avantages à nous rejoindre :
Key Qualifications & Skills
Technical Expertise – must-have :
Programming: Python (advanced); TypeScript/Java is a plus.
LLM Tooling: LangChain or LlamaIndex; prompt engineering; vector databases (PGVector, Weaviate, Milvus, Elastic, Pinecone).
Cloud & Containers: Kubernetes/OpenShift, Docker, Terraform; at least one major cloud (Azure preferred, AWS/GCP fine).
Data Engineering: ETL on structured & unstructured data, streaming (Kafka/PubSub), SQL optimisation.
MLOps: CI/CD for models, experiment tracking (MLflow/Weights & Biases), monitoring (Prometheus/Grafana).
Security & Compliance: OAuth2/OIDC (Keycloak), RBAC, secrets management, encryption in transit & at rest; familiarity with banking regulations.
Technical Expertise – nice-to-have
Retrieval algorithms beyond dense vectors (hybrid BM25 + embeddings).
Experience rolling out AI chat/agent products to external customers.
Knowledge of EU or MEA banking standards
Experience & Work Ethic:
5 + years in software or data engineering with 2 + years hands-on GenAI / NLP.
Proven ability to take fuzzy product ideas to production with minimal supervision.
Strong communication skills; comfortable presenting technical trade-offs to non-technical stakeholders.
Why Join Us?
Green-field GenAI stack: no tech debt—start with the latest research and tools.
Real-world impact: empower banks to launch compliant AI services their customers can trust.
Ownership & growth: shape the engineering culture inside a global group while staying in a tight, startup-like squad.
Hybrid work & Paris HQ: flexible policy with regular on-site workshops for deep collaboration.
Les avantages à nous rejoindre :
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