# Solutions Architect

**Company:** [Weekday AI](http://jobs.workable.com/companies/pxG9rDgnvZm2c86JUchT1j.md)
**Location:** Bengaluru, India
**Workplace:** on site
**Employment type:** Full-time
**Department:** Weekday's Client via platform

[Apply for this job](http://jobs.workable.com/view/58d24a26-7061-4577-abf8-fa2078dc7b08)

## 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.

## Requirements

### 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.