GenAI Lead

Essential functions

• Design, train, fine-tune, and optimize local LLMs or other NLP models for PII detection across diverse data types (documents, databases, knowledge graphs, code, and other knowledge-sharing formats).

• Develop generative AI agents (on Autogen/Langgraph) for schema- and metadata-based PII detection to enhance identification of sensitive data.

• Work with cutting-edge AI frameworks (Ray, llama.cpp, ollama, vLLM, PyTorch) to deploy and scale models efficiently in a distributed environment.

• Implement and optimize AI/ML solutions on Azure cloud and on-premise infrastructure, ensuring high performance and reliability.

• Collaborate with data engineering, security, and compliance teams to align AI solutions with business needs and regulatory requirements.

• Lead a small team of AI engineers, providing mentorship, code reviews, and technical guidance to drive project success.

• Maintain and monitor model performance, retraining models on a quarterly or monthly basis to handle 50+ PB of evolving data and to improve accuracy over time.

• Ensure AI models follow best practices and compliance standards, adhering to security requirements and regulations (GDPR, CCPA, PCI DSS, etc.).

Qualifications

• Strong experience with AI frameworks such as Ray, llama.cpp, ollama, vLLM, and PyTorch for building and scaling LLM solutions.

• Expertise in LLM fine-tuning and prompt engineering, including techniques like Reinforcement Learning from Human Feedback (RLHF) to refine model outputs.

• Hands-on experience with AI model deployment in Azure cloud environments as well as on-premises servers.

• Familiarity with large-scale data (50+ PB) and distributed computing paradigms (e.g., using clusters or Ray) to handle massive datasets.

• Familiarity with MCP (Model Context Protocol) Servers and securing them.

• Strong programming skills in Python, with experience in machine learning frameworks and libraries.

• Ability to work cross-functionally with stakeholders in security, compliance, and data engineering to incorporate their requirements into AI solutions.

• Strong awareness if not implementation experience with Differential Privacy/Federated Learning.

• Excellent communication skills, with the ability to explain complex AI concepts and results to non-technical teams and leadership clearly.

Would be a plus

• Proven experience leading small AI/ML teams, with a track record of delivering projects and mentoring team members.

• Knowledge of data security and compliance frameworks, as well as experience with responsible AI practices (ethical AI, bias mitigation, data privacy).

• Background in financial, payments, or security-related AI applications, giving you insight into the challenges and standards of the fintech industry.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office