This role is for one of the Weekday's clients

Min Experience: 3 years

Location: Bengaluru, India

JobType: full-time

As a Senior AI Developer / Architect, you won’t be handed rigid specifications—you’ll be driving innovation, architecture, and implementation across AI-driven systems that learn, adapt, and respond intelligently to user needs.

Requirements

Key Responsibilities:

• Design and build autonomous AI agents using LLMs/SLMs and Retrieval-Augmented Generation (RAG) techniques.
• Implement advanced agent behaviors including task decomposition, reasoning, and action planning (e.g., Chain-of-Thoughts, ReAct).
• Rapidly prototype and iterate on AI capabilities to create adaptive and intelligent user experiences.
• Leverage and contribute to frameworks such as LangChain, LlamaIndex, and others to power intelligent applications.
• Collaborate with UX, product, and engineering teams to bring AI features into production.
• Select, fine-tune, evaluate, and optimize models to meet performance, reliability, and scalability requirements.
• Contribute to the setup of robust AI/ML Ops pipelines for continuous delivery and lifecycle management of models.
• Ensure security and compliance in AI model development and data usage.
• Partner with data engineering teams to curate high-quality training and analysis datasets.

Required Skills & Qualifications:

• 3+ years of hands-on experience in AI/ML development and architecture.
• Demonstrated expertise in building LLM/SLM-based AI agents with real-world applications.
• Strong understanding of deep learning, NLP, reinforcement learning, and both supervised and unsupervised learning techniques.
• Familiarity with modern AI frameworks including LangChain, LlamaIndex, and similar libraries.
• Experience with model deployment and operationalization in production environments.
• Strong grasp of AI ethics, data privacy, and application security considerations.
• Excellent problem-solving skills and the ability to thrive in a collaborative, fast-paced environment.

Nice to Have:

• Experience in leading or assembling AI/ML Ops teams.
• Contributions to open-source AI frameworks or research.
• Background in deploying generative AI systems or intelligent assistants at scale.