# AI Architect > Weekday AI · Hyderabad, India · Full-time · Posted 2026-09-25 **Salary:** INR 4,000,000–7,000,000 **Workplace:** on_site **Department:** Weekday's Client via platform ## Description **This role is for one of Weekday’s clients Salary range: Rs 4000000 - Rs 7000000 (ie INR 40 - 70 LPA)** Min Experience: 10+ years Location: Hyderabad JobType: full-time We are looking for an AI Software Architect / Senior AI Engineer who is a self-starter and thrives on designing and delivering production-grade AI solutions powered by Large Language Models (LLMs). This role requires deep expertise in architecting, building, and operating complex AI systems, including Retrieval-Augmented Generation (RAG), agentic workflows, tool calling, evaluation frameworks, and observability platforms. The ideal candidate combines strong software engineering fundamentals with demonstrated experience delivering real-world AI products. Beyond experimentation, this individual must be capable of designing scalable, reliable, and cost-effective LLM-powered solutions that operate successfully in production environments. They should possess a strong understanding of modern AI architecture patterns, prompt engineering, retrieval systems, agent orchestration, and AI observability. ## Requirements ### Key Responsibilities - Own the architecture of AI-powered services and their integration with backend, mobile, and web applications. - Design, build, and maintain production-grade LLM applications using modern AI frameworks and orchestration platforms. - Lead technical design reviews and drive architectural decisions across AI services, backend systems, data pipelines, and cloud infrastructure. - Architect agentic workflows involving tool use, function calling, multi-agent systems, planning, memory management, and reasoning chains. - Establish evaluation frameworks to measure AI quality, reliability, latency, cost, and business impact. - Implement AI observability and monitoring using platforms such as Langfuse, LangSmith, OpenTelemetry, and related tooling. - Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases, embeddings, document pipelines, and retrieval optimization techniques. - Collaborate with software engineers, data scientists, product managers, and domain experts to translate business requirements into AI solutions. - Optimize prompts, retrieval strategies, model selection, and system architecture for accuracy, reliability, performance, and cost efficiency. - Design scalable APIs and services to expose AI capabilities across internal and external applications. - Define AI engineering standards, best practices, and governance processes across the organization. - Provide technical leadership and mentorship to engineers working on AI initiatives. - Leverage cloud platforms such as Google Cloud Platform (GCP) to deploy and scale AI services. - Document AI architectures, workflows, evaluation methodologies, and operational procedures. ### Qualifications - Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or related field. - 10+ years of software engineering experience with at least 5 years focused on LLM-based solutions and generative AI systems. - Demonstrated experience designing and deploying complex production-grade AI applications using Large Language Models. - Extensive experience with AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or equivalent technologies. - Hands-on experience implementing AI observability and evaluation frameworks using Langfuse, LangSmith, or similar platforms. - Proven expertise with Retrieval-Augmented Generation (RAG) architectures and vector database technologies. - Strong understanding of modern LLM architectures, prompting strategies, context management, embeddings, and retrieval techniques. - Strong Python development experience and software engineering fundamentals. - Experience designing scalable APIs and cloud-native architectures. - Ability to evaluate architectural trade-offs involving model performance, latency, reliability, maintainability, and cost. - Experience deploying AI solutions in production environments using Docker, Kubernetes, and cloud platforms. - Strong understanding of structured and unstructured data processing pipelines. - Familiarity with modern database technologies including PostgreSQL, vector databases, and document stores. - Excellent communication, leadership, and mentoring skills and ability to collaborate effectively with cross-functional teams. ### Preferred Skills - Experience building agentic systems involving tool use, planning, memory, and multi-agent orchestration and skills. - Experience with model evaluation, benchmarking, AI testing frameworks, and automated quality assessment. - Experience working with multiple commercial and open-source models including OpenAI, Anthropic, Gemini, Llama, and Mistral. - Familiarity with fine-tuning, synthetic data generation, and model optimization techniques. - Familiarity with developing and training machine learning models. - Experience supporting AI products in regulated, privacy-sensitive, or high-availability environments. - Experience integrating AI capabilities into mobile and web applications. - Familiarity with modern software delivery practices including DevOps, CI/CD, and Agile development methodologies. Must-have skills RAG, LLM, GCP Good-to-have skills Python, architecture ## Apply [Apply at Weekday AI](https://apply.workable.com/weekday-1/j/9DE799FDEE/apply) --- Powered by [Workable](https://www.workable.com)