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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 Show more Show less
