We are seeking an experienced Solution Architect with 15+ years of experience to design and deliver enterprise-grade cloud solutions with deep expertise in Qualtrics, AWS, and enterprise experience platforms. The role requires strong architecture, consulting, and client-facing experience to build scalable, secure, and AI-enabled solutions across industries including Banking, Telecom, Automotive, Healthcare, and Aviation.
Locations (2)
Mumbai, Maharashtra, India
Thane, Maharashtra, India
Responsibilities
Lead requirement discovery, solution scoping, effort estimation, and technical proposal creation.
Engage with business stakeholders to translate business requirements into scalable technical solutions.
Provide technical consulting during pre-sales and client presentations.
Design end-to-end cloud-native architectures using AWS and Qualtrics.
Architect enterprise integrations with CRM, analytics platforms, and enterprise applications.
Requirements
Bachelor's Degree in Computer Science or related technical discipline
Nice to have: AWS Certified Solutions Architect
Nice to have: Qualtrics CX/EX Certification
Nice to have: Agile/Scrum methodologies
Nice to have: Consulting or Professional Services background
The Agentic AI Builder designs, builds and industrialises AI agents and multi-agent workflows for Sia's enterprise clients, and helps users adopt them. You will turn real business processes into agents that perform reliably in production.
Responsibilities
Work with consultants and business teams to identify agent use cases and translate business processes into clear agent requirements and acceptance criteria.
Design agent architectures for business workflows, deciding when a single agent, a multi-agent pattern or a deterministic workflow with LLM steps is the right choice.
Implement orchestration, tool calling and control flow in Python using frameworks such as LangGraph, LangChain, the Claude Agent SDK or OpenAI SDK, or custom code where that is the better choice.
Build tools and connectors to enterprise APIs and data sources, including MCP servers, with clear schemas, error handling and permissioning.
Engineer context deliberately: retrieval over enterprise data, prompt and context design, and state and memory management across steps and sessions.
Requirements
Bachelor's degree in Computer Science, Engineering or a related field
Master's degree in Computer Science, Engineering or a related field
Nice to have: Model Context Protocol (MCP)
Nice to have: Multi-agent patterns (planner, executor, supervisor, handoff)
Mid-level Technical Analyst supporting Digital team in developing web, mobile, chat, and voice solutions.
Responsibilities
Assume leadership of collaboration with product ownership to translate business needs into the technical system requirements of the product.
Proactively identify requirement gaps and issue to product ownership.
Ensure non-happy path scenarios are considered and handled.
Advocate for solutions that consider ease of maintenance and component reuse opportunities.
Leverage available documentation and exercise test versions of applications and APIs to understand existing functionality to inform enhancement opportunities and creation of new capabilities.
Requirements
Nice to have: financial industry experience
Nice to have: native mobile application requirements
Highly experienced and strategic AI leader to drive the design, architecture, and implementation of enterprise AI solutions across global business operations. Leading development of scalable AI platforms, enterprise copilots, automation frameworks, and advanced analytics.
Compensation
competitive salary plus fully comprehensive benefits and performance bonus package based on an annual objective achievement.
Responsibilities
Define and lead enterprise AI architecture standards, frameworks, and best practices
Design scalable AI platforms supporting Generative AI, Agentic AI, Machine Learning, and advanced analytics
Establish enterprise governance for AI security, compliance, model lifecycle management, and responsible AI adoption
Partner, collaborate and influence senior leadership to identify high-value AI use cases aligned with business priorities and operational efficiency goals
Lead the end-to-end design and deployment of enterprise AI solutions and intelligent automation initiatives