Generative AI Practice Leader

• The Generative AI Practice Leader is accountable for driving growth, strategic positioning and to ensure success in the future (e.g., practice focus areas, offerings, capabilities).

• Extensive experience in Advisory, Solutioning, Presales, Delivery and Global experience.

Expectations

• Be the face of our Generative AI capabilities for clients in Life Sciences domain. Proactively work with Client Partners to grow Generative AI footprint in our clients and position Birlasoft as a leading solution provider in this space. Actively search for opportunities to expand business within existing accounts and help win new clients.
• Proactively develop differentiated Generative AI solutions & Service Offerings for Life Sciences domain and leverage similar solutions from other Verticals. Identify, assess, and develop Generative AI and AI/ML applications by applying key industry tools, techniques, and methodologies.
• Experience in Life Sciences (Pharma + MedTech) domain
• Building new technology capabilities, and building team competencies
• Manage business relationship with the technology partners & start-up eco systems and demonstrate edge over competition.
• Passionate about technology and customer success with excellent communication and articulation skills
• Ability to communicate technical concepts and solutions at a level appropriate for technical and non-technical audiences.
• Research, curate, and record tutorials on various applications of data science and machine learning, especially on Generative AI
• Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects.

Technical Skills

• Bachelor's or master's Degree
• Proven experience as an Enterprise Architect, Solution Architect, or a similar role, with a focus on AI/ML and generative AI.
• Strong understanding of generative AI techniques, including deep generative models, autoregressive models, and reinforcement learning for generative tasks.
• Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
• At least 5+ years of hands-on experience with building language models, machine learning and AI models leveraging industry tools, products, and / or Azure cognitive services.
• Deep and hands-on expertise in (as an individual contributor) Undertaking data collection, Data mining, preprocessing and analysis of structured and unstructured data.
• Hands-on expertise in large language models (LLMs/LSTMs/BERT) that can perform complex reasoning in few- and zero-shot settings by generating intermediate chain of thought (CoT) reasoning steps
• Experience of building / customizing and fine-tuning AI models including LLM models via OpenAI (Azure), Bert (AWS) for rapid PoCs
• Experience on LLM Model Governance, LLMSecOps, Hallucination and bias handling
• Deep and hands-on experience in applying machine learning algorithms.
• Strong data science and data engineering background both with open source and cloud distributed machines learning and AI tools especially Azure Cognitive Services, Azure Machine Learning and AWS Sagemaker and Bedrocks
• Strong understanding of Azure cloud technology including Cognitive Services viz. Vision, Speech, Language, Decision, Search and GenAI and its implementation