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Senior Applied AI Engineer at Weekday AI. This role is for one of the Weekday's clients. Salary range: Rs 6000000 - Rs 9000000 (ie INR 60-90 LPA). Min Experience: 7 years. Location: Remote (India). JobType: full-time. As a . Senior Applied AI Engineer. , you will be responsible for designing, building, and productionizing advanced AI systems powered by Large Language Models (LLMs) and intelligent agents. You’ll work on mission-critical capabilities such as AI Assistants, Autonomous Agents, Conversational Systems, Semantic Search, Search Personalization, Deep Research Agents, and AI-powered automation—driving measurable impact on user productivity at scale.. The role focuses on leveraging large-scale data and cutting-edge AI to predict user behaviors, personalize experiences, and optimize the customer journey through intelligent automation.. What You’ll Be Working On. AI Assistant & Agent Systems. . . Agent Architecture & Implementation:. Build sophisticated multi-agent systems capable of reasoning, planning, and executing complex workflows. . . . Context Management:. Design systems to maintain context across multi-turn conversations. . . . LLM & Agentic Platforms:. Develop scalable agentic frameworks and large language model platforms to enable widespread adoption. . . . Backend Systems:. Build and maintain robust back-end infrastructure to support AI agents. . . . AI Features:. Deliver solutions like Conversational AI, Semantic Search, and Personalized Content Generation. . . Classical AI/ML (Optional Focus). . Enhance recommendation systems, search relevance, and entity extraction models. . . Build intelligent matching engines and lookalike/recommendation systems. . . Key Responsibilities. . . Design & Deploy LLM Systems:. Deliver reliable, scalable production systems serving millions of users. . . . Agent Development:. Build advanced AI agents capable of chaining LLM calls, integrating APIs, and managing workflow states. . . . Prompt Engineering:. Develop, test, and optimize prompting strategies to maximize LLM effectiveness. . . . System Integration:. Create APIs and integrate AI features into existing infrastructures and external platforms. . . . Evaluation & QA:. Establish evaluation frameworks, monitoring systems, and A/B testing pipelines to ensure quality, safety, and reliability. . . . Performance Optimization:. Drive cost, latency, and scalability improvements across models and providers. . . . Collaboration:. Partner with product teams, backend engineers, and stakeholders to deliver business-driven AI solutions. . . Required Qualifications. Core AI/LLM Experience. . 7+ years of software engineering experience with production systems. . . 1.5+ years (2023–present) of hands-on experience building real-world LLM applications (GPT, Claude, Llama, etc.). . . Proven track record in delivering customer-facing, scalable LLM-powered products. . . Experience in multi-step agent development, workflow automation, and LLM chaining. . . Strong expertise in prompt engineering, few-shot learning, and optimization techniques. . . Technical Engineering Skills. . Expert-level proficiency in Python for production systems. . . Strong background in backend engineering, APIs, and distributed architectures. . . Familiarity with frameworks like LangChain, LlamaIndex, or similar. . . Proven experience with API integrations and cloud deployment (AWS, GCP, Azure). . . Quality & Evaluation. . Skilled in building evaluation frameworks for LLM accuracy, safety, and performance. . . Strong understanding of A/B testing methodologies. . . Hands-on experience with production monitoring, debugging, and reliability engineering. . . Experience managing data pipelines to support large-scale AI systems. . . What Makes a Great Candidate. . . Production-First Mindset:. Experienced in building AI systems used by real users, not just prototypes. . . . Technical Depth with Business Focus:. Ability to design end-to-end systems, balancing performance, scalability, and cost trade-offs. . . . Evaluation & Quality Excellence:. Track record of implementing measurable evaluation methodologies while prioritizing safety and UX. . . . Adaptability & Growth:. Comfortable working in ambiguous spaces, staying current with the evolving AI landscape, and adapting to new models and frameworks. . . Skills. Large Language Models (LLMs) • Generative AI • Prompt Engineering • Multi-Agent Systems • Conversational AI • Chatbot Development. Company Location: India.