Key Responsibilities

• Design, develop, and implement scalable and efficient Generative AI solutions across various business use cases.
• Contribute to initiatives focused on automation of complex operations such as SAR (Suspicious Activity Reports), KYC reviews, and fraud risk assessments.
• Guide and support cross-functional teams through all phases of solution development – from planning and PoC to deployment.
• Provide architectural leadership for AI/ML pipelines, ensuring seamless data integration and API connectivity.
• Evaluate and recommend best-in-class GenAI tools, frameworks, and methodologies (e.g., OpenAI, Hugging Face, TensorFlow).
• Manage project delivery and resource allocation, ensuring alignment with KPIs and business objectives.
• Continuously monitor project risks and implement effective mitigation strategies.
• Act as a trusted technical advisor, building strong client relationships and offering strategic input on AI initiatives.
• Stay informed on the latest trends in Generative AI, cloud-native technologies, and data science techniques.
• Identify opportunities for internal process improvements and proactively recommend solutions.
• Collaborate with stakeholders to generate hypotheses, build analytical models, and extract actionable insights.
• Analyze large, complex data sets to uncover patterns and trends using both supervised and unsupervised learning algorithms.
• Perform data wrangling, model tuning, and optimization to enhance performance and accuracy.

Required Skills & Qualifications

• 5+ years of experience in solution architecture, AI/ML development, and enterprise software engineering.
• Hands-on experience with Generative AI platforms and tools: OpenAI APIs, Hugging Face, TensorFlow, etc.
• Strong programming skills in Python (preferred), with additional experience in Java or similar languages.
• Proficiency with cloud platforms: AWS, Azure, or Google Cloud; experience in microservices architecture is a plus.
• Solid understanding of AI/ML pipelines, data integration, statistics, and API development.
• Experience with model development, testing, deployment, and performance tuning.
• Strong problem-solving and analytical skills.
• Excellent communication, presentation, and stakeholder management skills.
• Ability to manage multiple priorities in a fast-paced and dynamic work environment.

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