Exponentia.ai - Senior Engineer - Generative AI Solutions (4-7 yrs)

Job Responsibilities :

- Lead the development and deployment of Generative AI solutions using Databricks and advanced web frameworks.

- Architect and implement APIs to serve Generative AI models for production environments.

- Design end-to-end solutions for clients, focusing on GenAI applications, ensuring scalability and performance optimization.

- Provide expertise on pricing models, manage cost estimates, and develop Bill of Materials (BoM) for client projects.

- Collaborate with clients and internal teams to understand requirements and deliver tailored GenAI solutions.

- Document workflows, API structures, and architectural designs, ensuring transparency and clarity for all stakeholders.

- Effectively communicate with clients, providing regular updates on project progress and addressing any technical questions.

Required Skills :

- Minimum 7 years of relevant experience in AI/ML development and deployment.

- Proven experience developing and deploying end-to-end applications in production environments.

- Extensive hands-on experience with Databricks for building data pipelines and GenAI model development.

- Strong expertise in building and deploying APIs using modern web frameworks to serve GenAI models.

- In-depth knowledge of Generative AI models (e.g., GPT, LLAMA, Gemini, Anthropic and Open source models) and API integration.

- Experience conducting architecture and technical discussions with clients.

- Proficient in Python and libraries for GenAI (e.g., Hugging Face, OpenAI, Open source or custom-built transformer models).

- Experience with cloud platforms (preferably Azure/AWS) for deploying AI and GenAI solutions.

- Strong architectural skills for designing scalable and performant GenAI applications.

- Implement and integrate advanced LLM (Large Language Models) techniques, including LangChain, LlamaIndex, and other frameworks, for developing GenAI solutions.

- Apply prompt engineering techniques to optimize GenAI model outputs for specific client use cases.

- Ensure robust AI safety guardrails are in place during the development of Generative AI applications, focusing on prevention of unsafe outputs.