Solution Architect / Practice Lead – Retail Digital Commerce & GenAI
Work Location:
Hyderabad / Chennai
Aspire Systems (www.aspiresys.com) is a global technology services company that helps enterprises build and modernize digital products through engineering excellence, domain expertise, and customer-centric innovation. With deep capabilities across Digital Engineering, Cloud, Data, AI, Enterprise Applications, and Quality Engineering, Aspire partners with organizations to accelerate business transformation and deliver measurable outcomes.
About the Role
We are looking for a Solution Architect / Practice Lead – Retail Digital Commerce & GenAIto join our Retail business unit (www.aspiresys.com/retail)
This role will anchor solution architecture, pre-sales support, accelerator development, and client-facing consulting across digital commerce, store systems, customer experience, and emerging GenAI-led solutions.
Required Experience
- Overall 12+ years of experience in the IT Services.
- 8+ years in solution architecture, technical leadership, or enterprise application design.
- 5+ years of experience in retail, digital commerce, customer experience platforms, store systems, OMS, loyalty, merchandising, or adjacent domains.
- Practical experience in pre-sales, solution consulting, proposal support, or client-facing architecture discussions.
- Hands-on exposure to GenAI / LLM-based applications through POCs, pilots, internal accelerators, or production implementations.
The right candidate may come from one of these backgrounds:
- Retail Digital Commerce Architect who has started working on GenAI / AI-led use cases.
- Cloud / Microservices Solution Architect with retail domain exposure and recent GenAI hands-on experience.
- Pre-sales Solution Architect with strong technical depth and experience shaping POCs, demos, and proposals.
- Technical Practice Lead who can combine architecture, client consulting, and team enablement.
- We are not looking for a pure data scientist or research-only AI profile.
- This role needs a practical architect who can take business problems from idea to proposal to POC to production
GenAI / AI Application Exposure
Practical experience in some of the following:
- LLM-based application development using OpenAI, Azure OpenAI, Anthropic, Gemini, or similar.
- RAG / knowledge search patterns.
- Prompt engineering and grounding techniques.
- Vector databases or semantic search.
- AI assistants, copilots, chatbots, workflow automation, or agent-based POCs.
- Basic understanding of LLM evaluation, hallucination risk, access control, and cost considerations.
Retail / Digital Commerce
Experience in at least two of the following areas:
- Digital commerce platforms such as SFCC, commercetools, Adobe Commerce, Shopify Plus, Oracle Commerce, or similar.
- Store systems / POS / associate-facing applications.
- Order management, inventory, loyalty, customer service, or merchandising workflows.
- Search, personalization, product discovery, customer engagement, or commerce integrations.
- Retail data flows involving ERP, CRM, CDP, BI, or data warehouse platforms.
Core Architecture
- Strong understanding of enterprise application architecture.
- Java / Spring Boot / microservices experience.
- REST API design, integration patterns, and cloud-native architecture.
- Experience with at least one major cloud platform — Azure, AWS, or GCP.
- Familiarity with containers, CI/CD, environment planning, and production deployment considerations.
Consulting & Communication
- Ability to conduct discovery conversations and convert business needs into solution options.
- Strong proposal writing, estimation, and presentation skills.
- Ability to explain technology clearly to both technical and business stakeholders.
- Comfortable working with sales, delivery, engineering, and leadership teams.
Key Responsibilities
1. Solution Architecture & Consulting
- Design scalable enterprise solutions across retail digital commerce, store operations, customer service, order management, merchandising, and related retail workflows.
- Translate business problems into practical technology solutions using cloud-native architecture, APIs, microservices, integration patterns, data platforms, and AI/GenAI components.
- Define solution blueprints, architecture diagrams, effort estimates, implementation approaches, and delivery assumptions.
- Review technical feasibility, identify risks, and guide teams on pragmatic design choices.
2. GenAI / AI-Led Solutioning
- Lead solutioning for GenAI-enabled use cases such as conversational assistants, knowledge search, workflow automation, store associate enablement, customer service automation, and operational intelligence.
- Work with engineering teams to build and refine POCs using LLMs, RAG patterns, prompt engineering, vector search, APIs, and enterprise data sources.
- Evaluate where GenAI adds business value and where deterministic/rules-based approaches are more appropriate.
- Support responsible AI considerations such as access control, grounding, observability, evaluation, and cost management.
3. Pre-Sales & Proposal Support
- Partner with sales, account teams, delivery leaders, and practice teams to shape proposals, solution narratives, demos, and commercial models.
- Participate in discovery calls, client workshops, technical deep-dives, and executive presentations.
- Prepare solution decks, estimates, assumptions, implementation roadmaps, and proposal responses.
- Help convert early-stage opportunities and POCs into structured delivery engagements.
4. Practice & Accelerator Development
- Contribute to reusable accelerators, reference architectures, demo assets, case studies, and internal capability-building initiatives.
- Mentor engineers and consultants across digital commerce, cloud, and AI-led solution areas.
- Run or support internal practice cadences to track solution progress, reusable assets, technical learnings, and upcoming opportunities.
- Collaborate with cross-functional teams across delivery, infrastructure, data, cloud, UX, marketing, and sales.
5. Delivery Governance & Technical Leadership
- Provide architecture oversight during project initiation and early delivery phases.
- Support teams on environment setup, integration dependencies, CI/CD, cloud deployment, security considerations, and production-readiness.
- Work with delivery managers to ensure technical assumptions, scope boundaries, and risks are clearly understood.
- Help troubleshoot architecture-level blockers during POCs and early implementation cycles.
Good-to-Have Skills
These are desirable but not mandatory:
- Experience with agent frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar.
- Experience with AI observability, evaluation frameworks, or AgentOps concepts.
- Exposure to Snowflake, Databricks, Power BI, Looker, or enterprise data platforms.
- Knowledge of MACH architecture, composable commerce, headless commerce, or API-first commerce platforms.
- Experience building reusable accelerators, internal IP, demos, or technical whitepapers.
- Exposure to pricing models for cloud, AI tokens, infrastructure, or managed services.
- Experience working with US or global retail clients.
What Success Looks Like
Within the first year, the person should be able to:
- Lead solutioning for multiple retail technology and GenAI opportunities.
- Build credibility with client stakeholders through practical architecture and business-value framing.
- Support conversion of POCs into production engagements.
- Strengthen reusable accelerators and reference architectures.
- Mentor teams and improve internal capability around GenAI-enabled retail solutions.
- Partner effectively with sales, delivery, cloud, data, and engineering teams.
Why Join Us
This role offers the opportunity to work at the intersection of retail transformation, digital commerce, cloud architecture, and GenAI adoption. You will help shape next-generation solutions for enterprise retailers while contributing to reusable platforms, accelerators, and consulting capabilities.
You will work with senior leaders, architects, sales teams, and delivery teams to solve real business problems.
