GenAI Platform Data Engineer

● 5+ years of experience in software engineering, with significant hands-on experience building Generative AI / LLM-based solutions in production.

● Expert-level Python skills, including experience with modern GenAI frameworks (LangChain, LlamaIndex or equivalent).

● Deep understanding of LLM concepts: RAG architectures, embeddings, prompt engineering, fine-tuning and evaluation methodologies.

● Hands-on experience integrating LLM providers (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI) into production systems.

● Experience with vector databases (Pinecone, OpenSearch, FAISS, Weaviate) and embedding optimization.

● Solid cloud experience (AWS, Azure or GCP) for deploying and scaling AI workloads.

● Strong understanding of data security, privacy and regulatory considerations relevant to the banking / financial sector.

● Proven ability to lead technical initiatives and mentor engineering teams.

● Fluent English.

● Experience designing multi-agent or agentic AI workflows.

● Familiarity with AI observability tools (Langfuse, Weights & Biases, Helicone).

● Prior experience in banking, financial services or other highly regulated industries.

● Experience with MLOps practices and model governance frameworks.

● AWS, Azure or GCP ML/AI certifications, a plus.

● Degree in Computer Science, Software Engineering, AI/ML or a related field.

As a Senior / Lead GenAI Engineer, you will design, build and scale production-grade Generative AI solutions for a leading company in the banking sector, taking technical ownership from architecture through deployment, in a fully remote role.

We are looking for a Senior / Lead GenAI Engineer with deep, hands-on expertise in Python and Large Language Models to design, build and scale Generative AI solutions for a leading banking sector client. In this role, you will take technical ownership of GenAI initiatives end-to-end - from architecture and prototyping through to secure, compliant production deployment - while mentoring engineers and partnering with business, risk and compliance stakeholders to ensure solutions meet the standards of a highly regulated environment.

● Design, build and deploy production-grade Generative AI solutions (RAG pipelines, conversational assistants, multi-agent systems) using Python and modern LLM frameworks.

● Lead prompt engineering, chain-of-thought orchestration, structured output parsing, guardrails and evaluation pipelines for LLM-based applications.

● Architect and own RAG pipelines end-to-end: document ingestion, chunking, embeddings, vector store management and retrieval optimization.

● Deploy and operate GenAI applications on cloud infrastructure (AWS, Azure or GCP), with a focus on scalability, security and cost optimization.

● Implement evaluation and monitoring frameworks for AI systems: response quality, latency, hallucination detection and feedback loops.

● Define MLOps practices for LLM-based systems: versioning, automated evaluation and production monitoring.

● Act as technical lead for GenAI initiatives, mentoring engineers and setting technical direction.

● Translate business requirements from banking stakeholders (risk, compliance, customer experience) into robust technical solutions.

● Partner with architecture, security and compliance teams to ensure GenAI solutions meet the regulatory standards of the banking sector.

Fully remote position.