Solution Architect - Full Stack and AI

Quess Corp Limited; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Quess Corp Limited is seeking a hands-on Solution Architect with a strong full-stack background and AI feature experience. The role owns enterprise solution delivery from discovery through production, guiding engineering teams, prototyping integrations, and ensuring secure, scalable deployments.

The candidate should review code, design APIs, and coordinate across frontend, backend, AI, and DevOps teams to deliver production-ready architectures.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field preferred.
• Hands-on experience building production-grade web apps and AI-powered features.
• Strong backend and API design experience with scalable architectures.
• Experience integrating enterprise platforms and external APIs.

Responsibilities

• Understand requirements and translate into practical technical solutions.
• Own solution delivery from discovery to production rollout.
• Design scalable full‑stack apps, APIs, workloads, and AI features.
• Define system architecture, data flows, and deployment models.
• Build prototypes for complex integrations and AI use cases.
• Collaborate with frontend, backend, AI, DevOps, and customer teams.
• Review code, API contracts, and database models.

Skills

Full Stack Development

Solution Architecture

AI-powered features

API design

Code review

Cross-functional collaboration

Education

Bachelor's degree in CS or related field

Tools

Node.js

Python

Java

REST APIs

Docker

CI/CD

AWS/Azure/GC

Job description

Job Description: Solution Architect - Full Stack and AI

Role Overview

We are looking for a hands-on Solution Architect with a strong full-stack development background and experience building AI-powered product features.

The role will own enterprise solution delivery from requirement discovery and architecture design through development, integration, deployment, and production stabilization. This is not a documentation-only architecture role. The candidate should be comfortable reviewing code, building prototypes, solving integration issues, and guiding engineering teams through implementation.

Key Responsibilities

• Understand business requirements and convert them into practical technical solutions.
• Own solution delivery from discovery through production rollout.
• Design scalable full-stack applications, enterprise integrations, APIs, workflows, and AI-enabled features.
• Define system architecture, application components, data flows, integration patterns, and deployment models.
• Build prototypes and proof-of-concept solutions for complex integrations and AI use cases.
• Work closely with frontend, backend, AI, DevOps, and customer technology teams.
• Review code, architecture decisions, API contracts, database models, and implementation approaches.
• Design integrations using REST APIs, webhooks, event-driven systems, message queues, and scheduled processes.
• Build or guide the development of AI features such as conversational interfaces, document processing, intelligent search, recommendations, copilots, and workflow automation.
• Design secure and reliable integrations with enterprise systems and third-party platforms.
• Define authentication, authorization, data transformation, error handling, retries, monitoring, and audit logging.
• Identify technical risks, dependencies, and scalability constraints early in the delivery cycle.
• Support testing, deployment, troubleshooting, and post-production stabilization.
• Create reusable architecture patterns, components, integration templates, and engineering standards.

Required Experience

• Strong experience as a Full Stack Developer, Technical Lead, Solution Architect, or Engineering Lead.
• Hands-on experience building and delivering production-grade web applications.
• Strong backend experience with Node.js, Python, Java, or similar server-side technologies.
• Experience designing REST APIs, microservices, databases, authentication systems, and distributed applications.
• Experience integrating enterprise platforms, third-party applications, and external APIs.
• Hands-on experience building AI-powered features using large language models or machine learning services.
• Experience working with LLM APIs, prompt design, structured outputs, tool calling, retrieval-based systems, or agentic workflows.
• Understanding of relational and NoSQL databases, caching, queues, and search systems.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Understanding of Docker, CI/CD, application monitoring, and production deployment.
• Ability to translate business requirements into executable technical plans.
• Strong problem-solving, communication, and stakeholder-management skills.

Preferred Experience

• Experience building enterprise SaaS products or internal business platforms.
• Experience with HRMS,ERP, CRM, payroll, workforce management, finance, or operations systems.
• Experience with vector databases, embeddings, semantic search, RAG pipelines, or document intelligence.
• Familiarity with AI orchestration frameworks and agent development patterns.
• Experience with API gateways, middleware, iPaaS platforms, or event-streaming systems.
• Understanding of data privacy, access control, encryption, auditability, and enterprise security.
• Experience leading small engineering teams or coordinating delivery across multiple technical teams.

Expected Technical Profile

The ideal candidate should be able to:

• Design the complete solution architecture.
• Build or review front end and backend components.
• Create APIs and integration services.
• Prototype AI-powered product features.
• Evaluate technical trade-offs.
• Debug issues across the full application stack.
• Work directly with customers and enterprise technology teams.
• Take technical ownership until the solution is successfully deployed.

Success Measures

• Solutions are delivered within agreed scope and timelines.
• Architecture decisions translate cleanly into working software.
• AI features are useful, reliable, secure, and production-ready.
• Integrations remain scalable and maintainable after deployment.
• Technical risks and delivery blockers are identified early.
• Production issues are minimized and resolved quickly.

Education

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field is preferred. Equivalent hands-on engineering and product-building experience will also be considered.