What are the responsibilities and job description for the GenAI / Python / AI Developer position at VeriiPro?
Job Description
- 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.
- 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.
