Your role and responsibilities

• Design, develop, implement AI and Generative AI solutions to address business problems and achieve objectives. 
• Gather, clean, and prepare large datasets to ensure readiness for AI model training 
• Train, fine-tune, evaluate, and optimize AI models for specific use cases, ensuring accuracy, performance, cost-effectiveness, and scalability. 
• Seamlessly integrate AI models and autonomous agent solutions into cloud-based & on-prem products to drive smarter workflows and improved productivity. 
• Develop reusable tools, libraries, and components that standardize and accelerate the development of AI solutions across the organization. 
• Monitor and maintain deployed models, ensuring consistent performance and reliability in production environments 
• Stay up to date with the latest AI/ML advancements, exploring new technologies, algorithms, and methodologies to enhance product capabilities. 
• Effectively communicate technical concepts, research findings, and AI solution strategies to both technical and non-technical stakeholders. 
• Understand the IBM tool and model landscape and work closely with cross-functional teams to leverage these tools, driving innovation and alignment. 
• Lead and mentor team members to improve performance.  
• Collaborate with operations, architects, and product teams to resolve issues and define product designs. 
• Exercise best practices in agile development and software engineering.  Code, unit test, debug and perform integration tests of software components 
• Participate in software design reviews, code reviews and project planning. 
• Write and review documentation and technical blog posts. 
• Contribute to department attainment of organizational objectives and high customer satisfaction 

Required technical and professional expertise

• Minimum 6 years of hands-on experience developing AI-based applications using Python. 
• 2+ years in Performance testing, Reliability testing 
• 2+ years of experience using deep learning frameworks (TensorFlow, PyTorch, or Keras)  
• Solid understanding of ML/AI concepts: EDA, preprocessing, algorithm selection, machine learning frameworks, model efficiency metrics, model monitoring. 
• Familiarity with Natural Language Processing (NLP) techniques.  
• Deep understanding of Large Language Models (LLM) Architectures, their capabilities and limitations.  
• Proven expertise in integrating and working with LLMs to build robust AI solutions. 
• Skilled in crafting effective prompts to guide LLMs to provide desired outputs.  
• Hands-on experience with LLM frameworks such as Langchain,Langraph,CrewAI etc.,  
• Experience in LLM application development based on Retrieval-Augmented Generation (RAG) concept, familiarity with vector databases, and fine-tuning large language models (LLMs) to enhance performance and accuracy. 
• Proficient in microservices development using Python (Django/Flask or similar technologies). 
• Experience in Agile development methodologies 
• Familiarity with platforms like Kubernetes and experience building on top of the native platforms 
• Experience with cloud-based data platforms and services (e.g., IBM, AWS, Azure, Google Cloud). 
• Experience designing, building, and maintaining data processing systems working in containerized environments (Docker, OpenShift, k8s) 
• Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders

Preferred technical and professional experience

• Experience in MLOPs frameworks (BentoML,Kubeflow or similar  technologies) and exposure to LLMOPs 
• Experience in cost optimisation initiatives
• Experience with end-to-end chatbot development, including design, deployment, and ongoing optimization, leveraging NLP and integrating with backend systems and APIs. 
• Understanding of security and ethical best practices for data and model development 
• Contributions to open source projects