About the role
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 microservices architecture
- 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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