Staff Engineer (Generative-AI)

• Total experience 7+ Years.
• Deep understanding of Generative AI fundamentals and transformer-based architectures.
• Strong experience in Cloud Architecture (e.g., AWS, Azure, GCP) for deploying scalable AI systems.
• Proven experience with BERT, GPT, LLaMA, and similar LLMs.
• Strong hands-on experience in prompt engineering and RAG techniques.
• Experience in fine-tuning and deploying models using frameworks like Hugging Face Transformers, LangChain, or equivalent.
• Familiarity with multi-agent AI systems and collaborative model workflows.
• Proficient in Python and machine learning libraries (e.g., PyTorch, TensorFlow).
• Strong problem-solving skills and a passion for AI innovation and ethical development.
• Experience integrating models into enterprise platforms and APIs.
• Understanding of ML Ops practices and CI/CD pipelines for AI deployment.
• Background in Natural Language Processing (NLP) and Knowledge Engineering.
• Excellent communication skills, with the ability to articulate solutions effectively.

RESPONSIBILITIES:

• Understanding the clients business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the clients requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
• Understanding and relating technology integration scenarios and applying these learnings in projects
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.