AI Solution Engineer

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in AI/ML solution design and delivery, preferably in financial services or a regulated industry.
• Hands-on experience with LLMs (Large Language Models), agent frameworks, and AI orchestration tools (e.g., LangChain, AutoGen, Hugging Face).
• Strong systems design and solution architecture skills.
• Familiarity with cloud platforms (Azure, AWS, GCP), MLOps, and secure application deployment.
• Proficiency in Python and/or JavaScript; experience with REST APIs and integration patterns.
• Experience with version control (e.g., GitHub) and CI/CD pipelines.
• Understanding of AI evaluation metrics, interpretability, ethical AI, and compliance.
• Excellent cross-functional collaboration and communication skills; ability to translate business needs into technical solutions for both technical and non-technical stakeholders.
• Knowledge of financial services, wealth management, or regulatory environments is an asset.
• Experience with Agile delivery and rapid prototyping methodologies.
• Growth and enablement mindset: passionate about teaching, upskilling teams, and building a culture of responsible AI adoption.

Nice-to-Have Skills

• Experience with frontend frameworks (React, Angular, Vue) for building user-facing AI tools.
• Familiarity with authentication protocols (OAuth, SAML, JWT, TLS).
• Experience with data visualization tools (Tableau, Power BI, matplotlib).
• Exposure to prompt engineering and fine-tuning LLMs.
• Experience with containerization (Docker, Kubernetes) and cloud-native deployment.
• Prior work involving SaaS platform integrations or enterprise system integration.
• Previous Banking experience