Solutions Architect at Weekday AI

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

11 Sep, 26

Salary

15000000.0

Posted On

13 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Java, Spring Boot, Generative AI, Large Language Models, RAG Architectures, Microservices, Cloud-Native Applications, Distributed Systems, Prompt Engineering, AI Orchestration, System Design, API Standards, CI/CD, Observability, Technical Leadership, Stakeholder Management

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Salary range: Rs 8000000 - Rs 15000000 (ie INR 80-150 LPA) Experience: 12+ yrs Location: Bengaluru Job Type: full-time We are seeking an experienced Solution Architect with a strong background in Java, Spring Boot, and Generative AI to lead the design and delivery of next-generation AI-powered enterprise applications. This is a hands-on leadership role for a technology professional who combines deep software engineering expertise with practical experience building and deploying production-grade AI solutions. The ideal candidate will have extensive experience designing scalable distributed systems, architecting cloud-native applications, and integrating Large Language Models (LLMs) into business-critical products. You will work closely with engineering, product, design, and data teams to define technical strategy, build intelligent platforms, and drive innovation through Generative AI technologies. This role requires a balance of architectural leadership and hands-on engineering, with a strong focus on delivering high-quality, scalable, and reliable solutions that create measurable business impact. Key Responsibilities Design and architect scalable enterprise applications using Java, Spring Boot, microservices, and cloud-native technologies. Lead the development and deployment of Generative AI solutions, including LLM-powered applications, intelligent assistants, and AI-driven workflows. Design and implement Retrieval-Augmented Generation (RAG) architectures for knowledge retrieval and contextual AI experiences. Build and optimize prompt engineering frameworks, AI orchestration layers, and agent-based systems. Define system architecture, API standards, integration patterns, and engineering best practices. Drive end-to-end solution design from requirements gathering through implementation, deployment, and production support. Collaborate with product, engineering, and business stakeholders to translate business requirements into scalable technical solutions. Evaluate emerging AI technologies and identify opportunities to enhance products through automation and intelligence. Establish observability, monitoring, evaluation, and governance frameworks for AI systems in production. Lead architecture reviews, technical design discussions, and engineering decision-making processes. Mentor engineering teams and provide guidance on software architecture, design patterns, coding standards, and AI best practices. Support hiring and development of high-performing engineering talent, particularly within AI and platform engineering domains. Ensure security, scalability, reliability, and maintainability across all solutions and platforms. Drive continuous improvement through automation, CI/CD practices, performance optimization, and operational excellence. What Makes You a Great Fit 12+ years of software engineering experience with strong expertise in enterprise application development. Hands-on experience building production-grade Generative AI solutions using Large Language Models. Strong proficiency in Java and Spring Boot for designing and developing scalable backend systems. Deep understanding of RAG architectures, prompt engineering, AI orchestration, and agent-based workflows. Proven experience architecting distributed systems, APIs, microservices, and cloud-native applications. Strong software engineering fundamentals including system design, scalability, security, and performance optimization. Experience leading technical architecture initiatives and influencing engineering teams across multiple functions. Ability to balance strategic architectural thinking with hands-on technical execution. Strong understanding of AI evaluation frameworks, observability, monitoring, and production operations. Experience working closely with product, design, analytics, and engineering stakeholders to deliver business outcomes. Proven ability to mentor engineers, build high-performing teams, and foster technical excellence. Familiarity with cloud platforms, CI/CD pipelines, automation frameworks, and modern development practices. Strong communication and stakeholder management skills with the ability to explain complex technical concepts to both technical and non-technical audiences. Knowledge of responsible AI practices, governance, data privacy, and risk mitigation strategies is highly desirable. Experience in complex enterprise software, SaaS platforms, or data-intensive environments is an added advantage.

Responsibilities

Lead the design and delivery of scalable enterprise applications and production-grade Generative AI solutions. Define technical strategy, architect RAG frameworks, and mentor engineering teams to drive AI-powered innovation.