Senior Data / AI Engineer

ABOUT ALPIAN:
We are building the next generation of private banking — one that is digital, personalized, and meaningful.

Alpian is the first Swiss digital private bank, combining wealth management and everyday banking in a single mobile app. Our mission? Make investing and banking simple, intuitive, and accessible—without compromising on security, trust, or excellence.

To get there, we bring together bold thinkers, pragmatic engineers, and people who know how to deliver high-impact solutions.

If you like solving hard problems for real users, in production, you will feel right at home.

PURPOSE:
As a Senior AI Engineer, you will design, build, and operate production-grade AI systems that power Alpian’s next-generation banking experiences.

This role goes far beyond prompts and demos. You will apply strong software engineering discipline, data governance principles, and modern LLM techniques to deliver AI systems that are secure, observable, cost-aware, and trustworthy (i.e., the kind that belong in a regulated banking environment).

You will work at the intersection of LLMs, analytics, and data platforms, where BigQuery and analytical correctness matter just as much as agentic workflows.

Responsibilities

WHAT YOU'LL BE DOING:
• Design and implement LLM-powered platforms used by real customers and internal teams.
• Build agentic workflows with explicit state, tool/function calling, retries, and failure handling.
• Engineer robust (Agentic) RAG pipelines:

• Chunking and embedding strategies
• Metadata-aware retrieval and ranking
• Grounding

• Leverage analytics and data platforms as first-class AI inputs:

• Querying and modeling data in BigQuery
• Designing AI-friendly analytical schemas
• Ensuring correctness, consistency, and explainability of results

• Apply data governance and security best practices:

• PII handling and customer data isolation
• Access control, auditability, and traceability

• Make AI systems observable and measurable:

• Tracing, evaluations, and error analysis
• Latency and cost monitoring

• Write clean, maintainable Python code:

• Async APIs
• Proper testing strategies
• CI/CD pipelines and containerized deployments

• Act as a technical interface with stakeholders and partners, producing clear documentation and explaining trade-offs without hype.

• Provide clear technical documentation
• Explain trade-offs without hype or buzzwords 🙂

OUR STACK:
• Google ADK (Agent Development Kit)
• Google Vertex AI
• BigQuery (core analytical and AI data platform)
• Grafana (analytics, metrics, and data exploration)
• Python (async, APIs, testing, best practices)
• Vector databases & embedding models
• Cloud-native infrastructure on GCP
• CI/CD, containers, IAM, secrets management

Requirements

WHAT YOU'LL NEED:
• 5–8+ years of experience in software or platform engineering, with recent production LLM systems.
• Strong Python expertise, including async programming, API design, testing, and production debugging.
• Hands-on experience with agentic frameworks, such as:

• LangGraph / LangChain Agents
• AutoGen
• CrewAI
• LlamaIndex Agents
• (Bonus: Google ADK)

• Deep, practical experience with RAG engineering:

• Vector databases
• Chunking & embedding strategies
• Metadata-driven search and ranking

• Strong experience working with analytical data platforms, including:

• Writing and optimizing SQL queries
• Understanding analytical data models and metrics
• Using analytics outputs as reliable AI inputs

• Proven track record building secure, observable, and cost-aware AI systems:

• Tracing, evals, guardrails
• IAM, secrets, and PII-aware architectures

• Strong software engineering fundamentals:

• APIs, CI/CD, containerization
• Structured, maintainable codebases

• Clear communicator who can work across engineering, product, and business teams.

NICE TO HAVE:
• Experience designing multi-tenant AI systems
• Strong experience with the Google Cloud (Data) Platform:

• BigQuery
• Vertex AI Agent Engine
• Gemini Enterprise

• Experience integrating AI outputs with a dashboarding tool (e.g., Grafana, Looker) or analytics workflows
• Familiarity with ML evaluation frameworks or LLM-as-judge approaches
• Background in regulated environments (finance, healthcare, etc.)
• Strong opinions about software engineering and Python best practices (earned the hard way)

We care deeply about PRE-LLM EXPERTISE:
• data governance,
• ML fundamentals,
• evaluation rigor,
• and knowing when not to use an LLM.

WHY JOIN ALPIAN:
• Build the future of banking from the ground up
• A startup mindset backed by a full banking license
• A flat, collaborative, high-impact environment
• Hybrid setup, with base locations in Geneva or Lausanne

Ready to lead, empower, and build the bank of tomorrow? Apply now and let’s make it happen.