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Volante Technologies builds cloud-native payment and financial messaging software for banks and other financial institutions. Its Payments-as-a-Service offering, low-code integration platform, and API tools help clients connect payment systems, support domestic and cross-border transfers, and migrate to ISO 20022. The platform works with rails including FedNow, RTP, Fedwire, SWIFT, and SEPA, with capabilities for payment orchestration, preprocessing, and analytics. Volante Technologies operates in fintech and SaaS, serving enterprise banking clients worldwide.
Associate Director of Software Architecture
Lead architecture for Java, messaging, Kubernetes, and AI-enabled systems at Volante Technologies. The company provides low-code, cloud-based Payments as a Service for financial businesses.
विवरण
- Design and evolve scalable, reliable distributed systems, including AI and LLM components where appropriate.
- Select architectural patterns such as event-driven architecture, CQRS, Saga, Circuit Breaker, and API Gateway.
- Produce architecture blueprints, sequence diagrams, and technical specifications.
- Contribute to code reviews, technical discussions, and sprint ceremonies.
- Design and build messaging solutions with Apache Kafka, RabbitMQ, IBM MQ, and ActiveMQ.
- Apply Apache Camel to enterprise integration, routing, and transformation pipelines.
- Ensure messaging architectures deliver high throughput, fault tolerance, and required SLAs.
- Develop and review production-grade Java and Spring Boot code.
- Promote microservices practices for API design, service decomposition, and inter-service communication.
- Lead proofs of concept for frameworks, libraries, technologies, and AI or LLM approaches.
- Design and guide Docker and Kubernetes deployment strategies.
- Oversee Kubernetes workload orchestration, autoscaling, resource quotas, and namespace design.
- Work with DevOps and platform teams on CI/CD pipelines and infrastructure as code.
- Establish observability for distributed tracing, structured logs, and metrics.
- Set standards for performance monitoring and alerting.
- Profile and tune Java performance, including JVM, heap, and garbage collection.
- Lead benchmarking and address bottlenecks in high-traffic, latency-sensitive systems.
- Investigate JVM memory leaks and set memory-efficient programming practices.
- Design relational data models and optimize PostgreSQL, Oracle, or MySQL queries.
- Architect MongoDB schemas, indexes, and aggregation pipelines.
- Define data access patterns, connection pooling, and caching layers.
- Maintain data consistency, integrity, and resilience across distributed data stores.
- Identify technology gaps, prototype solutions with engineering teams, and turn PoC findings into architecture recommendations and implementation roadmaps.
- Mentor engineering teams through complex design and delivery challenges.
आवश्यकताएँ
- Bring 12–16 years of progressive, hands-on software engineering experience and a strong architecture track record.
- Remain actively involved in coding and engineering rather than working solely in management or advisory roles.
- Demonstrate expertise in Apache Kafka, RabbitMQ, IBM MQ, ActiveMQ, and Apache Camel.
- Show strong Java and Spring Boot skills for building enterprise-grade microservices and APIs.
- Have a record of designing large-scale distributed systems that handle high volumes and strict SLAs.
- Know Kubernetes and containerization well, including production cluster operations.
- Understand observability practices, including distributed tracing (such as Jaeger or Zipkin), logging (ELK/EFK), and metrics (Prometheus/Grafana).
- Understand JVM internals, memory management, and performance tuning techniques.
- Have solid experience with both relational databases (PostgreSQL, MySQL, Oracle) and NoSQL databases (MongoDB).
- Make architecture decisions based on established patterns and proven engineering principles.
- Have experience leading proofs of concept from start to finish.
- Use AI/LLM tools such as GitHub Copilot, ChatGPT, or Claude in day-to-day design, coding, reviews, documentation, and debugging.
- Be able to learn and implement AI/LLM solutions quickly and integrate them pragmatically into enterprise architectures when they provide clear value.
- Have experience in payments, financial messaging, or regulated financial technology platforms.
- Bring exposure to event sourcing and stream processing, such as Kafka Streams or Apache Flink.
- Have experience with chaos engineering and resilience testing practices.
- Have hands-on experience integrating LLM APIs or using AI frameworks such as Spring AI or LangChain4j in Java systems.
- Be familiar with vector databases or vector search, such as pgvector, Weaviate, Pinecone, or Milvus, and RAG patterns.
- Have exposure to responsible AI practices in production, including data governance, auditability, cost and latency monitoring, and human oversight where needed.
लाभ
- Competitive compensation.
- Health benefits.
- Remote or flexible work options.
- Professional development support.
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