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.
Requirements
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 AIPrompt EngineeringMulti-Agent SystemsConversational AIChatbot Development