AI Architect – Lead AI Solutions

About the role

We are looking for a hands‑on Lead AI Architect to design, develop and deploy production‑grade Machine Learning and Generative AI solutions for our banking and financial services clients. The role partners with business value streams to translate strategic objectives into scalable AI systems that deliver measurable business value.

Key responsibilities

• Design end‑to‑end AI/ML architectures that support scalability, real‑time inference and model governance.
• Develop, train and validate advanced models including deep learning, ensemble methods, transfer learning and large language models (LLMs).
• Build production‑grade pipelines with MLOps/AIOps practices, ensuring reproducibility, versioning and automated monitoring.
• Implement AI safety guardrails, compliance controls and responsible AI frameworks.
• Provide guidance to business units for AI use‑case development and drive adoption across the organization.
• Establish monitoring and governance processes for model drift, data drift and lifecycle management.

Required profile

• 10+ years of professional experience in AI/ML engineering, architecture or related roles.
• Proven delivery of at least three AI/ML solutions in production, preferably within enterprise or financial services environments.
• Demonstrated experience deploying Generative AI solutions (OpenAI GPT, Google Gemini, Mistral) and orchestration frameworks such as LangChain or LangGraph.
• Strong track record of translating business problems into AI opportunities and driving commercialization.

Required skills

• Python programming with clean‑code practices.
• FastAPI for building high‑performance APIs.
• Public cloud platforms: AWS, GCP, Azure (multi‑cloud a plus).
• Large Language Models (LLMs), prompt engineering, fine‑tuning, Retrieval‑Augmented Generation and agentic systems.
• MLOps/AIOps tooling and model lifecycle management.
• Vector databases, embeddings and semantic search.
• Model security, differential privacy, encryption and compliance with data‑privacy regulations.
• Bias detection, fairness metrics and explainable AI techniques.