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We are looking for an experienced Software Architect with deep expertise in designing and architecting large\-scale enterprise applications, as well as hands\-on experience with AI technologies and AWS Cloud. The ideal candidate should have strong proficiency in at least one backend technology stack — Java or Python — along with solid experience in cloud\-native architectures, distributed systems, AI/ML\-driven solutions, and AWS services.
This is a high\-impact, strategic role involving technical leadership, solution design, and architectural decision\-making across complex enterprise environments, with an emphasis on integrating AI and cloud capabilities into modern applications. **Key Responsibilities*** + Enterprise Architecture: Lead end\-to\-end architecture design for enterprise\-grade applications using Java or Python.
+ System Design: Define system architecture, integration patterns, microservices, and cloud\-native solutions.
+ API \& Distributed Systems: Design API frameworks, asynchronous systems, and scalable distributed architectures.
+ AWS Cloud Solutions: Architect and implement solutions leveraging AWS services such as EC2, Lambda, S3, RDS, DynamoDB, and SageMaker for AI/ML workloads.
+ Cloud Security \& Compliance: Ensure secure, compliant, and cost\-optimized use of AWS cloud resources.
+ Technical Leadership: Provide technical leadership and guide development teams across multiple projects.
+ Technology Evaluation: Evaluate and recommend technology stacks, frameworks, and architectural approaches.
+ Architecture Governance: Conduct architecture reviews, performance tuning, and security assessments.
+ Documentation: Create and maintain High Level Design (HLD) and Low\-Level Design (LLD) documentation.
+ Cross\-team Collaboration: Collaborate with Product, QA, DevOps, Security, and UI/UX teams for seamless delivery.
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+ Best Practices: Promote design patterns, code quality, CI/CD, and cloud adoption.
+ Mentorship: Mentor engineering teams and support technical decision\-making across the organization.
+ Technology Trends: Stay up to date with emerging technologies, cloud trends, and modern application architectures.
+ Model Deployment: Collaborate with data scientists to operationalize machine learning models in production environments.
+ Data Strategy: Define data pipelines, governance, and storage solutions for AI workloads.
+ Responsible AI: Ensure fairness, transparency, and compliance in AI adoption.
+ AI Automation: Identify opportunities to leverage AI for predictive analytics, intelligent automation, and decision support.
+ Monitoring \& KPIs: Establish KPIs and monitoring frameworks for AI systems to ensure accuracy and scalability.
+ Security \& Risk: Assess risks related to AI deployment, including bias, adversarial attacks, and data privacy.
+ Innovation: Stay ahead of advancements in generative AI, LLMs, and applied machine learning.
+ Enablement: Mentor teams on AI concepts, tools, and frameworks to foster innovation.
Core Technologies (any one stack):* + Java (Spring Boot, Spring, Hibernate/JPA)
+ Python (Django, Flask, FastAPI)
+ RESTful API design and integration patterns
+ Messaging systems (Kafka, RabbitMQ, Service Bus, etc.)
+ OOP, SOLID principles, DDD, and clean architecture
+ Docker, Kubernetes
+ Infrastructure\-as\-Code (Terraform, CloudFormation)
+ NoSQL: MongoDB, Cassandra, Redis
+ Excellent analytical and problem\-solving skills
+ Clear communication and documentation capability
+ Ability to lead and influence engineering teams and stakeholders
+ Strategic mindset with focus on scalability, reliability, and performance
+ MBA from IIM preferred for candidates applying under the 3–5\-year relevant experience criteria