GenAI Engineer - Banking; m​/f​/d

GenAI Engineer (Conversational AI, RAG & Agentic AI) Role Overview

We are seeking a highly skilled GenAI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions, with a strong focus on Conversational AI, Retrieval-Augmented Generation (RAG), and Agentic AI architectures
.

This role will be responsible for building intelligent AI-powered experiences that leverage large language models, knowledge retrieval systems, and multi-agent orchestration frameworks to solve complex business challenges. The successful candidate will work closely with business stakeholders, architects, data teams, and engineering teams to build scalable, secure, and production-ready AI solutions.

The ideal candidate will possess strong AI/ML fundamentals, hands-on experience with modern GenAI frameworks, and expertise in designing agent-based systems capable of reasoning, collaboration, and task execution.

• Design, develop, and deploy enterprise-grade Generative AI and Conversational AI solutions
• Build and optimize RAG (Retrieval-Augmented Generation) architectures to enhance AI response accuracy and grounding
• Develop and manage document and data ingestion pipelines for knowledge retrieval systems
• Design and implement vector search solutions using embeddings and vector databases
• Develop intelligent conversational experiences, chatbots, copilots, and virtual assistants
• Design and implement Agentic AI architectures
  , including autonomous and collaborative agent workflows
• Build and manage orchestrator-based multi-agent systems for complex task execution and decision-making
• Implement agent governance mechanisms, including agent registries and agent lifecycle management
• Develop and support Agent-to-Agent (A2A) communication protocols and agent collaboration frameworks
• Define customer journeys, user goals, intent classification, and routing strategies for conversational systems
• Collaborate with product, business, and engineering teams to translate requirements into AI-driven solutions
• Ensure AI solutions meet enterprise standards for scalability, reliability, security, and governance
• Contribute to AI model evaluation, prompt engineering, testing, and continuous improvement initiatives

• Strong understanding of AI/ML fundamentals and Generative AI concepts
• Hands-on experience designing and implementing RAG architectures
• Experience working with:
  • Embeddings
  • Vector Databases
  • Semantic Search
  • Hybrid Search Architectures
• Experience building and managing document and data ingestion pipelines
• Strong expertise in Conversational AI development
• Proven experience designing and implementing Agentic AI solutions
• Experience with:
  • Multi-Agent Systems
  • Agent Orchestration Frameworks
  • Agent Registries
  • A2A (Agent-to-Agent) Communication Protocols
• Strong understanding of user journey mapping, goal-oriented workflows, and intent routing strategies
• Experience with Python and GenAI frameworks such as Lang Chain, Lang Graph, Semantic Kernel, CrewAI, or equivalent
• Knowledge of REST APIs, cloud-native architectures, and AI deployment best practices
• Strong analytical, problem-solving, and stakeholder management skills

• Experience working with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic Claude, or Google Gemini
• Knowledge of AI governance, guardrails, evaluation frameworks, and Human-in-the-Loop (HITL) patterns
• Experience with vector databases such as Pinecone, Weaviate, Qdrant, ChromaDB, or Azure AI Search
• Exposure to MCP (Model Context Protocol) and advanced agent tooling frameworks
• Experience deploying AI solutions within enterprise or regulated environments
• Understanding of MLOps, LLMOps, CI/CD, and observability frameworks
• Experience in banking, financial services, or large-scale digital transformation programmes is preferred