Our client is a global consulting firm building and deploying production AI systems for major banking clients. They are looking to hire multiple AI engineers at Manager, senior manager or associate director level. These roles sit at the intersection of engineering and delivery — designing scalable agentic solutions, leading technical implementation, and owning the path from prototype to production. You’ll work across the full stack: LLM architecture, RAG pipelines, MLOps, CI/CD, and regulatory compliance, collaborating with data scientists, architects, and senior client stakeholders to ship AI that works at enterprise scale.
Core requirements
- Proven software or data engineering background, with a track record of applied AI delivery using Python and SQL
- Experience in banking or broader financial services
- Solid grasp of LLM fundamentals — prompt engineering, fine-tuning, embedding models, and RAG patterns
- Hands-on experience with at least one vector database (e.g. Pinecone) and at least one agent framework (e.g. LangChain, LangGraph, or Agent Development Kit)
- Ability to design and build evaluation frameworks for agentic systems
- Comfortable building API-enabled backend services, e.g. FastAPI
- MLOps or LLMOps knowledge, including CI/CD pipeline setup for ML or agent development
- Experience with at least one hyperscaler stack — AWS, Azure, GCP, or Databricks; cloud certifications preferred
- Familiarity with Agile or SaFe delivery methodologies
The role also requires
- Senior stakeholder management — translating technical concepts clearly for non-technical audiences
- Experience scoping and estimating agentic AI builds, including commercial thinking around ROI
- Dependent on level, confidence contributing to bids, RFPs, and proposal development
- Experience managing and developing junior team members
Client-facing and delivery-led. You’ll manage teams, shape proposals, and own outcomes.
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