This role is for one of the Weekday's clients
Salary range: Rs 8000000 - Rs 13000000 (ie INR 80-130 LPA)
Min Experience: 10 yearsLocation: Remote (India)JobType: full-timeAs 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.
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: 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
