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Job Description

AI Evangelist (Hands-On) – Financial Services

We’re seeking a senior, hands-on AI Evangelist to help drive AI adoption across a major financial organization. This role blends technical expertise, architectural leadership, and the ability to communicate AI value clearly to stakeholders ranging from engineering teams to executive leadership.

What You’ll Do

Build and showcase AI-driven solutions for financial use cases such as trading, risk, forecasting, or automated decisioning. Translate advanced AI concepts into practical insights for both technical and non-technical teams. Lead internal enablement: workshops, training sessions, and AI literacy programs. Provide advisory guidance to senior leaders on AI strategy and emerging technologies. Partner with compliance, risk, and technology teams to ensure solutions meet financial regulatory standards. Prototype, validate, and deploy AI models and agentic workflows into production. Maintain technical quality across AI-generated and human-written code, including reviews, testing, and documentation. Mentor engineering teams and contribute to best practices for integrating generative and agent-based AI in the SDLC.

Skills & Experience (Mandatory)

Degree in Computer Science, Data, Finance, or related field. Strong hands-on expertise in Python, SQL, and modern AI/ML frameworks (TensorFlow, PyTorch). Experience with at least one major backend (Java, C++, C#, Go). Working knowledge of Typescript/Node.js and modern UI frameworks. Proven track record in AI/ML roles within finance, fintech, or consulting, especially in regulated environments. Deep understanding of AI governance, ethics, guardrails, compliance, and data privacy. Experience building or deploying LLM-powered systems, agentic workflows, and code- pipelines. Strong capability in code review, automated testing, and maintaining quality across AI-assisted codebases. Exceptional communication and stakeholder engagement abilities—comfortable presenting to leadership. Ability to manage multiple initiatives with attention to detail and strategic alignment.

Nice-to-Have Skills

Exposure to RAG frameworks, vector databases, embeddings, and graph/temporal data systems. Familiarity with cloud-based deployment (AWS/Azure), containerization, and observability tooling. Experience with prompt engineering, model fine-tuning, quantization, or optimization techniques. Knowledge of multi-agent orchestration platforms, AI-enabled SDLC tools, or automated documentation pipelines. Participation in industry forums, conferences, or AI thought-leadership initiatives. Background applying AI to banking, investment, insurance, or other high-compliance sectors.

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