Staff AI engineer at Weekday AI

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

08 Mar, 26

Salary

0.0

Posted On

08 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Generative AI, LLM Development, Model Optimization, Python, Distributed Training, ML Frameworks, Chatbots, Content Generation, Model Lifecycle Management, Prompt Engineering, Dataset Curation, Evaluation Metrics, Model Observability, Technical Leadership, Mentoring

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients As a Staff AI Engineer, you will be responsible for the design, development, and deployment of cutting-edge AI models with a core focus on GenAI, LLM fine-tuning, and model optimization. You will lead research and experimentation initiatives, evaluate emerging technologies, and collaborate closely with product, engineering, and data science teams to deliver AI-driven solutions. Your responsibilities include architecting scalable systems, establishing best practices for model development, and ensuring robust performance across the AI lifecycle. You will push the boundaries of AI innovation, leveraging modern frameworks, vector databases, retrieval approaches, and distributed systems. This role is ideal for someone who thrives in high-ownership environments, enjoys solving complex technical problems, and has the ability to influence and mentor teams. Key Responsibilities Lead end-to-end development of Generative AI and LLM-based solutions, from ideation and architecture to deployment and optimization. Design and implement scalable AI/ML pipelines, including data ingestion, preprocessing, training, fine-tuning, evaluation, and monitoring. Collaborate with cross-functional teams to integrate AI capabilities into products and platforms. Conduct research on emerging AI trends, model architectures, embeddings, and retrieval-augmented generation (RAG) techniques. Optimize LLM performance through fine-tuning, prompt engineering, quantization, distillation, and model compression strategies. Establish best practices for AI model governance, explainability, reproducibility, and responsible AI development. Develop robust evaluation frameworks to measure model accuracy, fairness, safety, and system reliability. Work with vector databases, embeddings, and indexing techniques to support knowledge-driven workflows. Mentor engineering and data science teams, fostering technical excellence and innovation. Ensure scalable deployments using cloud platforms, containerization, and distributed systems. Participate in architectural design discussions and provide technical leadership to drive AI strategy and long-term roadmaps. What Makes You a Great Fit 9+ years of experience in AI/ML engineering, with at least 3–4 years focused on Generative AI or LLM development. Deep hands-on expertise with LLMs, RAG systems, embeddings, transformers, and model lifecycle management. Strong proficiency in Python, distributed training, model optimization, and ML frameworks such as PyTorch or TensorFlow. Experience building real-world GenAI applications including chatbots, content generation tools, conversational systems, or agent-based architectures. Proven ability to architect scalable AI systems and optimize model performance for production environments. Strong understanding of prompt engineering, dataset curation, evaluation metrics, and model observability. Ability to collaborate effectively with stakeholders, translate business problems into AI solutions, and drive technical strategy. Excellent problem-solving skills, communication abilities, and a passion for innovation. Experience mentoring teams and guiding complex technical decisions.

Responsibilities

Lead the development of Generative AI and LLM-based solutions, overseeing the entire process from ideation to deployment. Collaborate with cross-functional teams to integrate AI capabilities and establish best practices for model governance.