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Salary
≈ $50k – $106k per year (Estimated)
Location
Remote (India)
Seniority
Staff · 10+ years exp

First seen by Alion on Aug 27, 2026.

Overview
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Profile match
Genzeon is a healthcare AI company with automation solutions enhancing efficiency, accuracy, and compliance for modern medical operations.

Technical Architect

Location : Hyderabad / Pune Hybrid

Department : Retail

Experience : ~15 years overall, including 6 - 8 years in an Architect-level role

About the Role :

We are looking for an experienced Technical Architect to define and govern the technology strategy that connects business objectives with IT execution within the Retail domain. The role will own the overall technology architecture across applications, data, infrastructure, security, cloud, and AI/GenAI capabilities.


The ideal candidate will have strong experience in Python, cloud-native architecture, microservices, APIs, distributed systems, and AI/ML/GenAI, along with the ability to translate complex business requirements into scalable and future-ready technology solutions. You will work closely with business stakeholders, product teams, engineering leaders, data science teams, and senior technology teams to drive architecture strategy, modernization, cloud adoption, and AI/GenAI transformation across the retail technology landscape.

Key Responsibilities :

- Define and maintain the Technical Architecture vision, principles, standards, and roadmap aligned with retail business strategy.

- Own architecture across business, application, data, technology/infrastructure, security, and AI/ML layers.

- Design scalable, resilient, and secure architectures for large-scale, distributed, multi-system retail environments.

- Evaluate and select technology platforms, frameworks, tools, and technologies while maintaining the organization's technology reference stack.

- Lead architecture reviews and governance boards, ensuring solution designs align with organizational standards and minimize duplication and technical debt.

- Partner with business stakeholders, CxOs, product owners, and engineering leaders to translate retail capabilities such as eCommerce, POS, supply chain, order management, inventory, CRM, and payments into technology roadmaps.

- Guide cloud strategy and migration across AWS, Azure, and GCP, including hybrid and multi-cloud architectures.

- Define integration patterns using REST APIs, event-driven architecture, messaging, microservices, and integration platforms across retail systems and third-party platforms.

- Drive the design and adoption of Python-based services, APIs, automation solutions, data pipelines, and AI/ML applications where appropriate.

- Evaluate Python frameworks and technology stacks for enterprise applications, APIs, microservices, automation, and AI/GenAI use cases.

- Assess build-vs-buy decisions and lead vendor and technology evaluations.

- Drive modernization of legacy retail applications and define migration strategies with minimal business disruption.

- Establish architecture documentation standards including reference architectures, Architecture Decision Records (ADRs), capability maps, and technology standards.

- Mentor solution architects, technical leads, and senior engineers and act as a technical escalation point.

- Ensure architecture decisions address scalability, security, compliance, cost optimization, observability, and operational resilience, particularly during peak retail events and high-traffic periods.

- Stay current with emerging technologies and evaluate their applicability to the retail business.

- Define and drive the organization's AI/GenAI architecture strategy, identifying high-value use cases across personalization, demand forecasting, conversational commerce, supply chain optimization, fraud detection, and intelligent automation.

- Establish reference architectures for integrating AI/ML and GenAI capabilities, including LLMs, RAG pipelines, recommendation engines, model-serving platforms, and AI-enabled applications.

- Partner with data science, analytics, and engineering teams to ensure AI initiatives are built on governed, scalable, and secure data architectures.

- Define responsible AI guardrails covering data privacy, security, model governance, compliance, and responsible AI practices.

- Evaluate AI platforms, LLM providers, cloud-native AI services, MLOps tools, and GenAI frameworks as part of technology and build-vs-buy decisions.

Required Qualifications :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- Approximately 15 years of experience in software/IT, including 6 - 8 years in an Architecture role.

- Proven experience designing architectures for large-scale, distributed, multi-system enterprise environments, preferably within the Retail domain.

- Strong proficiency in Python, with experience designing and developing Python-based services, APIs, automation solutions, data pipelines, and AI/ML applications.

- Strong knowledge of at least one major cloud platform : AWS, Azure, or GCP, along with cloud-native architecture patterns.

- Strong experience with microservices, REST APIs, event-driven architecture, messaging, and enterprise integration patterns.

- Experience with Python frameworks and libraries such as FastAPI, Flask, Django, PyTorch, TensorFlow, or equivalent, depending on the solution requirements.

- Strong understanding of data architecture, security architecture, DevOps, CI/CD, and cloud infrastructure.

- Experience driving legacy modernization, application transformation, and cloud migration initiatives.

- Familiarity with enterprise architecture frameworks such as TOGAF, Zachman, or similar.

- Working knowledge of AI/ML concepts and AI-driven application architecture, including model serving, data pipelines, ML platforms, and GenAI application patterns.

- Understanding of LLM, RAG, vector databases, prompt engineering, and AI/GenAI integration patterns.

- Excellent stakeholder management and communication skills, with the ability to communicate effectively with both engineering teams and executive leadership.

- Strong understanding of architecture principles related to scalability, availability, security, performance, resilience, and cost optimization.

Preferred Qualifications :

- TOGAF or relevant cloud architecture certification such as AWS Certified Solutions Architect Professional or Azure Solutions Architect Expert.

- Prior experience in the Retail domain, including eCommerce platforms, POS systems, inventory management, order management, payments, or supply chain technology.

- Strong hands-on exposure to Python-based enterprise applications, microservices, APIs, automation, and data/AI pipelines.

- Experience with Python-based frameworks such as FastAPI, Flask, Django, PyTorch, TensorFlow, Pandas, or equivalent technologies.

- Hands-on exposure to GenAI/LLM-based solutions such as copilots, chatbots, RAG-based search, recommendation systems, or intelligent automation deployed in production.

- Experience with LangChain, LlamaIndex, vector databases, RAG architectures, or similar GenAI technologies.

- Background in Domain-Driven Design (DDD) and enterprise integration patterns.

- Familiarity with MLOps, ModelOps, AI governance, and data governance frameworks.

- Experience designing and implementing AI/ML platforms and scalable data pipelines.

- Experience with AI-driven retail use cases such as personalization engines, demand forecasting, conversational commerce, fraud detection, and supply chain optimization.

- Certifications in AI/ML or cloud AI platforms, such as AWS Machine Learning or Azure AI certifications, are a plus.

Key Technology Areas :

- Architecture : Enterprise Architecture, Solution Architecture, TOGAF, DDD, Architecture Governance

- Programming : Python

- Cloud : AWS / Azure / GCP

- Application Architecture : Microservices, REST APIs, Event-Driven Architecture, Messaging

- Integration : APIs, Enterprise Integration, Third-Party Integrations

- Data : Data Architecture, Data Pipelines, Data Governance

- AI/ML : Machine Learning, GenAI, LLMs, RAG, Model Serving, Recommendation Engines

- GenAI Technologies : LangChain, LlamaIndex, Vector Databases, Prompt Engineering

- DevOps : CI/CD, Cloud-Native Architecture, Automation, Observability

- Security : Application Security, Cloud Security, Data Privacy, AI Governance

- Retail : eCommerce, POS, Inventory, Order Management, Supply Chain, Payments, CRM

Skills

Technical Architect, REST API, AWS, Distributed Systems, Python, Microservices Architecture, Django, Flask, AI Integration, Generative AI, Application Architecture

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