You will be mainly accountable for:

• Optimization and Tuning: Drive the optimization, fine-tuning, and continuous improvement of large-scale LLMs, employing advanced techniques such as model distillation, pruning, quantization, and prompt engineering to maximize performance and reduce latency. 
• Agentic AI Development: Develop and deploy autonomous agentic AI systems capable of operating in dynamic, complex environments, with a focus on autonomy, decision-making, and task delegation. 
• API Development: Design, build, and optimize robust, high-throughput APIs for seamless integration of AI models into mission-critical enterprise applications. 
• AI Security and Compliance: Ensure adherence to strict coding standards and security protocols while developing AI systems, with a focus on data privacy, security, and compliance with regulatory frameworks. 
• Advanced Python and Design Patterns: Apply advanced Python techniques, including asynchronous programming, parallel processing, and distributed computing, to optimize the performance of AI models and systems. Implement and enforce the use of design patterns to ensure clean, maintainable, and scalable code. 
• Ethical and Responsible AI: Advocate and implement ethical AI practices, ensuring that all AI systems comply with responsible AI guidelines, fairness, transparency, and bias mitigation frameworks. 
• Collaboration & Mentorship: Collaborate with cross-disciplinary teams to deliver impactful AI solutions and mentor junior engineers, guiding them in adopting best practices in AI development and deployment. 
• Cutting-Edge Research: Stay at the forefront of AI research, integrating the latest advancements in NLP, reinforcement learning, and generative models into existing systems, driving innovation within the organization. 
• End-to-End Deployment: Manage end-to-end deployment and continuous integration pipelines, ensuring AI models are production-ready and scalable. Leverage cloud-based infrastructures such as Azure for high-availability deployment. 

You will join a dynamic team, where you will be able to thrive.

Qualifications for the role

• Proven Experience: 4+ years of hands-on experience designing, deploying, and optimizing large-scale production AI systems, with a strong track record of working with Gen AI and LLM architectures (e.g., GPT, T5, BERT, etc.). 
• Expert Knowledge in Agentic AI: Expertise in developing agentic AI systems with complex decision-making abilities and autonomous operations in dynamic environments. 
• Deep LLM Expertise: Mastery in Large Language Models and techniques for optimization and fine-tuning, including experience with transformer architectures, transfer learning, and model efficiency methods (distillation, pruning, quantization). 
• Design Patterns & Code Quality: Deep familiarity with software design patterns and clean code principles, along with an emphasis on building scalable, maintainable, and testable AI systems. 
• AI Security & Compliance: Strong understanding of AI-related security risks, data privacy, and compliance, with experience implementing solutions that align with regulatory standards (GDPR, HIPAA, etc.). 
• Cloud Infrastructure: Proven experience deploying and scaling AI applications using cloud-based infrastructures (AWS, GCP, Azure) and familiarity with containerization technologies like Docker and Kubernetes. 
• Research & Development: Ability to drive innovation by applying the latest research in AI, particularly in areas such as reinforcement learning, unsupervised learning, and self-supervised learning. 
• Collaboration & Leadership: Strong teamwork and communication skills with a demonstrated ability to lead teams, provide mentorship, and collaborate across technical and business units.
• Preferred Qualifications: 
• Experience working with cutting-edge NLP frameworks like GPT-4, OpenAI, or other state-of-the-art generative models. 
• In-depth experience with distributed AI systems, parallel computing, microservices, serverless compute and high-performance model training on GPU/TPU clusters. 
• Familiarity with advanced data governance frameworks and techniques for AI model interpretability and explain ability.