1. Development

• Design, develop, and deploy end-to-end AI applications, including scalable and production-ready systems.
• Build and integrate RESTful APIs and microservices to expose AI functionalities.
• Implement data ingestion, extraction (including OCR), and preprocessing pipelines for structured and unstructured data (text, images, documents).
• Develop and maintain vector databases, embedding pipelines, and chunking strategies for efficient semantic retrieval.

2. Models & Fine-Tuning

• Build and optimize LLM-based solutions using Prompt Engineering, RAG architectures, and fine-tuning techniques.
• Develop and apply machine learning models (regression, classification, clustering) for predictive analytics.
• Work on computer vision and image processing models using tools such as OpenCV, OCR frameworks, and deep learning-based image models.
• Continuously improve model performance through evaluation, hyperparameter tuning, and feedback loops.

3. Research & Innovation

• Stay current with advancements in AI/ML, NLP, Computer Vision, and Generative AI ecosystems.
• Explore and experiment with new techniques in prompt engineering, RAG optimization, and LLM architectures.
• Propose innovative solutions to enhance automation, accuracy, and scalability of AI systems.

4. Use Case Development

• Collaborate with stakeholders to understand business requirements and translate them into AI solutions.
• Design and develop chatbots, virtual assistants, and domain-specific AI applications.
• Create tailored AI workflows for content generation, document processing, and intelligent automation.

5. Quality Assurance

• Implement testing and validation frameworks to ensure AI model reliability and accuracy.
• Analyse outputs for relevance, coherence, and performance, and refine models/prompts accordingly.
• Establish monitoring mechanisms for production AI systems to ensure consistent performance.
• Document processes, workflows, and best practices for maintainability and knowledge sharing.

Qualifications

• Bachelor’s or master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field (Ph.D. is an advantage).
• 3+ years of experience in AI/ML, Natural Language Processing, or related domains.
• Strong proficiency in Python and experience with AI/ML and NLP libraries (e.g., Hugging Face, spaCy, OpenCV).
• Proven understanding of Large Language Models (LLMs) such as GPT, BERT, and their real-world applications.
• Hands-on experience in Prompt Engineering, RAG architectures, chatbot development, and AI system integration.
• Experience with machine learning algorithms (regression, classification, clustering) and model evaluation techniques.
• Familiarity with image processing and computer vision techniques, including OCR and deep learning-based image models.
• Experience in designing and deploying APIs and scalable AI solutions.
• Strong analytical, problem-solving, and communication skills with the ability to work in cross-functional teams.

Knowledge, Skills & Experience

• Experience working with cloud platforms (AWS, Azure, or Google Cloud) and AI/ML services.
• Proficiency in machine learning and deep learning frameworks (TensorFlow, PyTorch).
• Hands-on knowledge of vector databases, embeddings, chunking strategies, and semantic search systems.
• Understanding of advanced AI techniques such as reinforcement learning and model fine-tuning.
• Experience in building end-to-end AI systems, including data pipelines, model deployment, and monitoring.
• Familiarity with UX principles and the ability to design AI systems aligned with user needs and behaviours.
• Awareness of AI ethics, model bias, and responsible AI practices.

Personal Attributes

• Demonstrates a strong commitment to continuous learning and skill development in emerging AI technologies.
• Detail-oriented, diligent, and dependable in following established processes and standards.
• Professional demeanour with strong interpersonal and collaboration skills.
• Ability to work independently, troubleshoot issues, and deliver solutions proactively.
• Highly organized with effective time management and communication abilities.
• Capable of working under timelines and delivery targets in a dynamic environment.
• Strong team player with the ability to work across multidisciplinary teams with minimal supervision.
• Acts as a role model by demonstrating organizational values and professional behaviours.