We are seeking a highly experienced Architect to lead the design and delivery of scalable, high-performance platforms across backend engineering, data engineering, and AI/ML solutions. This role will define architecture strategy, guide engineering teams, and drive innovation in data-driven and AI-enabled products.

In this role you will...

Architecture & Design

• Define end-to-end architecture for distributed systems using Java and Python ecosystems
• Design scalable, secure, and high-availability systems (microservices, event-driven architectures)
• Establish best practices for system design, coding standards, and performance optimization
• Lead architecture reviews and provide technical governance
  

Backend Engineering (Java & Python)

• Architect and guide development of backend services using:
• Java (Spring Boot, reactive frameworks)
• Python (FastAPI, Flask, data/AI pipelines)
• Ensure API design standards (REST/GraphQL) and system interoperability
• Optimize system performance, reliability, and scalability
  

Data Engineering

• Design and implement modern data platforms (batch + real-time processing)
• Architect data pipelines using tools like Spark, Kafka, Airflow
• Define data modeling strategies (OLTP, OLAP, lakehouse architectures)
• Ensure data quality, governance, and lineage
  

AI / Machine Learning

• Architect AI/ML solutions including:
• Predictive models
• NLP / Generative AI use cases
• Collaborate with data scientists to productionize models (MLOps)
• Design scalable inference pipelines and model deployment strategies
• Evaluate and integrate emerging AI technologies
  

Cloud & DevOps

• Lead cloud-native architecture on AWS/Azure/GCP
• Define CI/CD pipelines and DevOps practices
• Ensure containerization and orchestration (Docker, Kubernetes)
• Drive infrastructure-as-code and automation strategies
• Leadership & Stakeholder

You have what it takes if you have...

• 12+ years of experience in software engineering, with 5+years in architecture roles
• Strong expertise in: Java (Spring ecosystem)
• Python (backend + data/AI)
• Deep knowledge of distributed systems and microservicesarchitecture
• Hands-on experience with data engineering frameworks(Spark, Kafka, Airflow)
• Experience with AI/ML systems and production deployment
• Strong understanding of cloud platforms (AWS/Azure/GCP)
• Proven ability to design scalable, fault-tolerant systems

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