Senior Generative AI scientist

Weekday; Pune District; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Weekday in India is seeking a Senior Generative AI Scientist to lead the design and deployment of conversational and voice intelligence solutions, integrating LLMs with real-world applications and building robust retrieval‑augmented generation pipelines.

You will mentor junior scientists, collaborate with product and data teams to define AI roadmaps, ensure observability and responsible‑AI practices, and present strategic insights to senior leadership to shape the company’s AI strategy.

Qualifications

• 6+ years of experience in applied AI with a focus on conversational and voice AI systems.

Responsibilities

• Lead the research, design, and implementation of conversational AI models powering chat, voice, and multimodal interfaces.
• Develop and maintain end-to-end RAG systems, including data curation, semantic indexing, and retrieval heuristics.
• Implement observability frameworks for LLMs, monitoring latency, hallucination rates, and bias indicators.
• Conduct rigorous A/B testing and real-world validation to refine model outputs and user experiences.
• Mentor junior scientists and data engineers, fostering a culture of experimentation and continuous learning.
• Collaborate with cross-functional teams to define product roadmaps and quantify AI impact on key business KPIs.
• Spearhead the adoption of open-source and proprietary tools for model training, evaluation, and deployment in cloud environments.
• Drive the creation of guidelines and policies for responsible AI, ensuring regulatory and ethical compliance.
• Engage with academic and industry communities to stay abreast of emerging research and technologies.
• Present findings and strategic insights to senior leadership, shaping the organization’s AI strategy.

Job description

This role is for one of the Weekday's clients

Salary range: Rs 2500000 - Rs 5000000 (ie INR 25-50 LPA)

Experience: 6+ yrs

Location: pune, bangalore, chennai

As a Senior Generative AI Scientist, you will spearhead the design and deployment of cutting‑edge conversational and voice intelligence solutions, driving the integration of large language models with real‑world applications. You will architect and optimize retrieval‑augmented generation pipelines, ensuring robust LLM observability and performance at scale. Collaborating closely with product, engineering, and data teams, you will translate business challenges into AI-enabled products that deliver measurable impact. Your role will involve continuous experimentation, model fine‑tuning, and the development of best‑practice guidelines for responsible AI use.

Key Responsibilities

• Lead the research, design, and implementation of conversational AI models that power chat, voice, and multimodal interfaces.
• Develop and maintain end‑to‑end RAG systems, including data curation, semantic indexing, and retrieval heuristics.
• Implement observability frameworks for LLMs, monitoring metrics such as latency, hallucination rates, and bias indicators.
• Conduct rigorous A/B testing and real‑world validation to refine model outputs and user experiences.
• Mentor junior scientists and data engineers, fostering a culture of experimentation and continuous learning.
• Collaborate with cross‑functional teams to define product roadmaps and quantify AI impact on key business KPIs.
• Spearhead the adoption of open‑source and proprietary tools for model training, evaluation, and deployment in cloud environments.
• Drive the creation of guidelines and policies for responsible AI, ensuring compliance with regulatory and ethical standards.
• Engage with academic and industry communities to stay abreast of emerging research and technologies.
• Present findings and strategic insights to senior leadership, shaping the organization’s AI strategy.

What Makes You a Great Fit

• 6+ years of experience in applied AI, with a strong focus on conversational and voice AI systems.
• Proven expertise in building and scaling RAG pipelines, leveraging retrieval techniques and knowledge graphs.
• Deep knowledge of LLM architecture and the ability to implement observability and monitoring solutions.
• Hands‑on experience with major frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) and cloud platforms (AWS, GCP, Azure).
• Strong programming skills in Python, along with proficiency in data engineering tools such as Apache Spark or Dask.
• Track record of publishing research papers or delivering open‑source contributions in AI and NLP domains.
• Excellent collaboration and communication skills, with the ability to translate technical concepts to non‑technical stakeholders.
• Demonstrated leadership in guiding cross‑functional teams through end‑to‑end AI projects from ideation to production.
• Ability to think strategically about AI product roadmaps and articulate long‑term vision.
• Passion for staying current with AI advancements and integrating the latest innovations into practical solutions.