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Weekday AI

Java Tech lead - AI

Weekday AI · Hyderabad, Telangana, India · ₹2M–₹4M/yr

Technology, Information and Internet · 11-50 employees

5 h ago
Principal (10+ yrs) Full-time India
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About the role

Design and architect scalable, secure enterprise applications using Java and microservices while integrating AI-native capabilities like RAG and LLMs. Lead technical roadmaps, conduct architecture governance, and mentor engineering teams to ensure high-performance software delivery.

What they look for

Java Spring Boot Microservices AI-Native Architecture LLM RAG Agentic AI Azure OpenAI Solution Architecture REST APIs CI/CD Distributed Systems Spring Batch Cloud-Native Design DevOps Prompt Orchestration

Requirements

Requires 9+ years of software development experience with 3-5 years specifically in a Solution Architect role. Must have deep expertise in Java, Spring Boot, and hands-on experience with Generative AI frameworks and Azure AI services.

Full description

This role is for one of the Weekday's clients

Salary range: Rs 2500000 - Rs 3500000 (ie INR 25-35 LPA)

Experience: 9+ yrs

Location: Hyderabad, Bengaluru

Job Type: Full-Time

We are seeking an experienced Java Solution Architect with expertise in AI-native architecture to design and deliver scalable, secure, and cloud-native enterprise applications. The ideal candidate will possess deep knowledge of Java technologies, microservices architecture, and modern cloud platforms, along with hands-on experience building intelligent applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and cloud-based AI services.

In this role, you will lead architectural decisions, define technical roadmaps, and collaborate with cross-functional teams to build high-performance, future-ready solutions. You will play a key role in driving architecture governance, mentoring engineering teams, and ensuring best practices across application design, AI integration, scalability, security, and deployment.

Key Responsibilities• Design and architect scalable, secure, and high-performance enterprise applications using Java, Spring Boot, REST APIs, and Microservices.

  • Define end-to-end solution architecture and prepare High-Level Design (HLD) and Low-Level Design (LLD) documentation.
  • Lead technical architecture discussions, design reviews, and governance across multiple engineering teams.
  • Build AI-native solutions leveraging Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Agentic AI frameworks, and intelligent orchestration patterns.
  • Integrate enterprise applications with cloud-based AI services, including Azure AI and Azure OpenAI, to deliver Generative AI capabilities.
  • Design scalable AI solutions with effective context management, memory handling, and prompt orchestration strategies.
  • Collaborate with business stakeholders, product teams, architects, and developers to translate business requirements into robust technical solutions.
  • Mentor engineering teams by providing guidance on architecture, coding standards, design patterns, and software engineering best practices.
  • Conduct architecture and code reviews to ensure solution quality, performance, security, and maintainability.
  • Drive DevOps adoption by implementing CI/CD pipelines, automated deployments, and cloud-native delivery practices.
  • Ensure adherence to enterprise architecture standards, security guidelines, and scalability requirements throughout the development lifecycle.

What Makes You a Great Fit• 9+ years of experience in software development, with significant experience designing enterprise-scale applications and distributed systems.

  • 3–5 years of experience as a Solution Architect or Technical Architect leading enterprise application architecture across cloud and on-premises environments.
  • Strong expertise in Java, Spring Boot, REST APIs, Microservices, Spring Batch, and enterprise application development.
  • Hands-on experience building AI-native applications using LLMs, RAG, Agentic AI frameworks, AI memory management, and Generative AI solutions.
  • Experience integrating Azure AI services, including Azure OpenAI, into enterprise applications.
  • Strong understanding of software architecture principles, design patterns, scalability, distributed systems, and cloud-native architectures.
  • Experience with DevOps tools, CI/CD pipelines, Git, Maven, and modern software delivery practices.
  • Familiarity with cloud platforms, enterprise security, and application performance optimization.
  • Knowledge of Linux environments, deployment automation, and RPM packaging is an added advantage.
  • Excellent analytical, communication, and stakeholder management skills with the ability to influence technical decisions.
  • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.
  • A collaborative leader with a passion for innovation, technical excellence, and building intelligent, scalable enterprise solutions.