Responsibilities:

• Lead the design, development, and deployment of generative AI based solutions.
• Collaborate with cross-functional teams to identify and implement AI solutions for client projects.
• Develop and maintain scalable AI infrastructure and pipelines.
• Conduct research to stay up-to-date with the latest advancements in AI and machine learning.
• Provide mentorship and guidance to junior AI engineers and team members.
• Optimize solutions for performance, scalability, and efficiency.
• Document methodologies, processes, and results for internal and external stakeholders.
• Engage with clients to understand their needs and provide tailored Generative AI solutions.

Experience and Qualifications:

• Minimum of 5 years of experience in software engineering, development and design, with a recent focus on AI, machine learning and specifically Generative AI.
• Bachelor’s or Master’s degree in Software Engineering, IT, Computer Science, or a related field.
• Strong theoretical understanding of AI and machine learning principles.
• Proven practical experience in developing and deploying AI/ML projects.
• Expertise in Generative AI, including LLMs, Transformers, and RAG.
• Hands-on experience with large language models and related tasks such as indexing, retrieval, and agent development.
• Working knowledge of some of the key platforms and enablers in the Generative AI ecosystem such as Microsoft Co-Pilot Studio, OpenAI, Google Gemini and Studio Bot, Ollama, LlamaIndex, and LangChain.
• Excellent problem-solving skills and the ability to devise innovative AI-powered solutions.
• Strong proficiency in programming languages such as Python, Java, Node, with a focus on machine learning frameworks (e.g., TensorFlow, PyTorch, etc.).
• Proficiency in SQL
• Strong collaboration and communication skills to work effectively in a team environment.

Good to Have Qualifications:

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with containerization technologies like Docker and Kubernetes.
• Knowledge of data engineering and ETL processes.
• Experience in data engineering while devising and implementing AI/ML solutions.
• Experience with reinforcement learning and deep learning frameworks.
• Understanding of ethical AI practices and considerations.
• Prior experience in a client-facing and team management role