Ai Tech Lead

We are seeking an experienced AI Tech Lead to drive the design, development, and implementation of AI solutions within a banking environment. The successful candidate will provide hands-on technical leadership, guide AI engineering teams, and deliver scalable, secure, and reliable AI applications aligned with business objectives.

Responsibilities

• Lead the architecture, development, testing, and deployment of AI and Generative AI solutions for banking use cases.
• Translate business requirements into scalable technical solutions and AI system designs.
• Drive the development of AI/ML models, LLM-powered applications, RAG pipelines, and AI agents where appropriate.
• Establish engineering best practices for code quality, testing, CI/CD, MLOps, and LLMOps.
• Integrate AI solutions with enterprise applications, APIs, databases, and existing banking systems.
• Ensure AI solutions meet requirements for security, data privacy, model explainability, performance, and regulatory compliance.
• Collaborate with business stakeholders, data scientists, engineers, architects, and risk teams to deliver AI initiatives.
• Mentor engineers, conduct code reviews, and provide technical guidance throughout the software development lifecycle.
• Monitor AI solution performance and drive continuous improvement in accuracy, scalability, reliability, and cost efficiency.

Requirements

• 7+ years of experience in software engineering, AI/ML engineering, or related technical roles, with demonstrated technical leadership experience.
• Strong programming skills in Python and experience with modern software engineering practices.
• Hands-on experience building and deploying AI/ML solutions in production environments.
• Practical experience with Generative AI, Large Language Models (LLMs), prompt engineering, RAG, vector databases, and AI application frameworks.
• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Strong understanding of APIs, microservices, distributed systems, databases, and enterprise application integration.
• Experience with MLOps/LLMOps, automated testing, CI/CD, model monitoring, and production deployment.
• Familiarity with AI security, data governance, model risk management, and responsible AI principles.

Preferred Qualifications

• Experience in banking, financial services, or other highly regulated industries.
• Familiarity with banking security standards, data privacy requirements, and AI governance frameworks.
• Experience deploying enterprise AI solutions using platforms such as Azure OpenAI, AWS Bedrock, or equivalent technologies.
• Knowledge of agentic AI, AI orchestration frameworks, and enterprise-scale AI architecture.