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.
Don't tick every box? If you meet around 70% of the requirements above, we'd still encourage you to apply.
About The 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.
Key Responsibilities
GenAI Solution Design & Delivery
- 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.
Platform & MLOps
- 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.
Leadership & Stakeholder Management
- 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.
Required Skills & Experience
- 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.
NICE TO HAVE
- 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.
EDUCATION
- Degree in Computer Science, Software Engineering, AI/ML or a related field.
Preferred Certifications
- AWS, Azure or GCP ML/AI certifications, a plus.
WORKING MODEL
Fully remote position.