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Staff Applied AI Engineer at Weekday AI. This role is for one of the Weekday's clients. Salary range: Rs 8000000 - Rs 13000000 (ie INR 80-130 LPA). Min Experience: 10 years. Location: Remote (India). JobType: full-time. As a Staff Applied AI Engineer, you will be responsible for building and productionizing advanced AI systems powered by Large Language Models (LLMs) and intelligent agents. You will work on mission-critical capabilities such as AI Assistants, Autonomous AI Agents, Deep Research Agents, Conversational Interfaces, Semantic Search, Search Personalization, and AI-driven automation—delivering features that directly impact millions of users’ productivity.. The mission of the AI Engineering team is to leverage large-scale data and cutting-edge AI to predict user behaviors, personalize experiences, and optimize every stage of 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:. Develop systems that maintain conversational context across multi-turn interactions. . . . LLM & Agentic Platforms:. Build scalable large language model and agentic platforms that drive adoption of AI-powered systems. . . . Backend Systems:. Develop scalable backend infrastructure to support AI assistants and agents. . . . AI Features:. Work on Conversational AI, Natural Language Search, Personalized Content Generation, and similar applications. . . Classical AI/ML (Optional Focus). . . Search Scoring & Ranking:. Enhance recommendation systems and search relevance algorithms. . . . Entity Extraction:. Build models for entity classification and automated keyword extraction. . . . Lookalike & Recommendation Systems:. Develop matching engines and intelligent suggestion systems. . . Key Responsibilities. . . Design & Deploy Production LLM Systems:. Deliver scalable, reliable AI systems that serve millions of users. . . . Agent Development:. Create advanced AI agents that chain multiple LLM calls, integrate with APIs, and maintain state across workflows. . . . Prompt Engineering:. Design and optimize prompting strategies, balancing fine-tuning and advanced prompting techniques. . . . System Integration:. Build robust APIs and integrate AI features into existing infrastructure and external platforms. . . . Evaluation & QA:. Implement evaluation frameworks, A/B testing, and monitoring systems to ensure accuracy, reliability, and safety. . . . Performance Optimization:. Optimize systems for latency, scalability, and cost across different LLM providers. . . . Collaboration:. Partner with product teams, backend engineers, and stakeholders to translate business requirements into technical solutions. . . Required Qualifications. Core AI/LLM Experience. . 10+ years of software engineering experience focused on production systems. . . 1.5+ years (2023–present) of hands-on experience building real-world LLM-powered applications (GPT, Claude, Llama, or others). . . Proven experience in building customer-facing, scalable LLM applications beyond prototypes. . . Strong expertise in multi-step AI agent development, LLM chaining, and workflow automation. . . Deep understanding of prompt engineering, few-shot learning, and optimization techniques. . . Technical Skills. . Expert-level Python programming for production AI systems. . . Strong backend engineering skills with scalable APIs and distributed architectures. . . Experience with LangChain, LlamaIndex, or similar frameworks. . . API integration expertise to enable advanced AI functionality. . . Experience deploying and managing AI systems in cloud environments (AWS, GCP, Azure). . . Quality & Evaluation Focus. . Hands-on experience with evaluation frameworks for LLM systems (accuracy, safety, and performance). . . Strong knowledge of A/B testing and experimental design. . . Experience in production monitoring, debugging, and reliability engineering. . . Skilled in managing scalable data pipelines to support AI systems. . . What Makes a Great Candidate. . . Production-First Mindset:. You’ve built and scaled AI systems used by real customers—not just research projects. . . . Technical Depth with Business Impact:. Ability to design end-to-end solutions while balancing cost, scalability, and performance trade-offs. . . . Evaluation & Quality Excellence:. Focus on measurable performance, safety, and user experience. . . . Adaptability & Learning:. Comfortable with ambiguity, rapidly evolving frameworks, and staying ahead of the AI landscape. . . Skills. Large Language Models (LLMs) • Generative AI • Prompt Engineering • Multi-Agent Systems • Conversational AI • Chatbot Development. Company Location: India.