Senior AI Engineer

Quick Facts

• Role: Senior AI Engineer (AI & Data Engineer)

Description

Build production-ready AI and data infrastructure that powers a next-generation WealthTech platform by transforming fragmented financial data into trusted, AI-ready data products. You will design and maintain AI-powered backend services, data pipelines, automated validation/reconciliation workflows, and LLM-based applications using RAG and AI agent orchestration. Optimize AI solutions for accuracy, reliability, latency, and cost while working with cross-functional teams.

Responsibilities

• Design, build, and maintain AI-powered services and backend applications
• Develop ETL/data pipelines to ingest, validate, normalize, enrich, and transform financial data
• Implement automated data validation and reconciliation processes, including AI agent-based workflows for data inconsistency detection and resolution
• Build and optimize LLM-based applications, AI agents, RAG solutions, and orchestration workflows
• Develop APIs and services exposing AI-ready financial data objects
• Create prompt engineering strategies, model evaluation/benchmarking, and observability
• Evaluate and optimize AI solutions for accuracy, reliability, latency, token usage, and cost
• Collaborate with Product and Engineering to translate business requirements into scalable solutions
• Contribute to scalable cloud-native architecture and backend services design
• Write clean, maintainable, and well-tested production code
• Participate in code reviews and architecture discussions; drive continuous improvement
• Support deployment, monitoring, troubleshooting, and performance optimization
• Continuously evaluate new models, AI technologies, frameworks, and best practices

Requirements

• 4+ years of professional software engineering experience with a strong background in backend, data, ML, or AI engineering
• FinTech/WealthTech/banking experience or experience working with financial data
• Strong Python programming
• Production-grade backend applications and API development experience
• Hands-on experience with modern LLMs including AI agents, agentic workflows, RAG architectures, and orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, Semantic Kernel)
• Experience with prompt engineering plus model evaluation and testing
• Experience working with databases
• Understanding of data engineering concepts and ETL/data pipelines
• Cloud platform experience (preferably Azure)
• Knowledge of REST APIs and distributed systems
• Strong problem-solving and ability to work independently
• Very good English communication skills

Benefits

• Flat organizational structure with fast decision-making and minimal bureaucracy
• Opportunity to work on innovative, tech-driven projects in the financial sector
• Private medical care (Medicover) and Multisport card
• Strong team culture with integration events, offsites, and regular team lunches
• Flexible working hours with a hybrid/remote setup (minimum 8 days per quarter in the office)