V

Volante Technologies

Cloud-native PaaS for real-time payments

Associate Director - Software Architecture

Backend EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • 12 to 16 years of progressive hands-on experience in software engineering with a strong architecture track record.
  • Remain active in coding and engineering rather than working purely in management or an advisory capacity.
  • Demonstrable expertise in Apache Kafka, RabbitMQ, IBM MQ, ActiveMQ, and Apache Camel.
  • Strong proficiency in Java and Spring Boot for building enterprise-grade microservices and APIs.
  • Experience designing large-scale distributed systems that handle high volumes and strict service-level agreements.
  • Deep knowledge of Kubernetes and containerization, including production cluster operations.
  • Expertise in observability practices, including distributed tracing such as Jaeger or Zipkin, logging such as ELK or EFK, and metrics such as Prometheus or Grafana.
  • Strong understanding of Java Virtual Machine internals, memory management, and performance tuning techniques.
  • Experience with relational database management systems including PostgreSQL, MySQL, or Oracle, and NoSQL databases including MongoDB.
  • Ability to make architecture decisions grounded in established patterns and proven engineering principles.
  • Experience conducting and leading proof-of-concepts end to end.
  • Comfort using AI and large language model tools such as GitHub Copilot, ChatGPT, or Claude in day-to-day design, coding, reviews, documentation, and debugging.
  • Ability to quickly understand, learn, and implement AI- and large language model-based solutions and pragmatically integrate them into enterprise architectures when they add clear value.

Responsibilities

  • Design and evolve large-scale distributed systems focused on scalability, reliability, and performance, including AI- and large language model-enabled components where appropriate.
  • Make architectural decisions based on proven patterns such as event-driven architecture, command query responsibility segregation, Saga, Circuit Breaker, and API Gateway; apply similar rigor to AI integrations, including guardrails, fallbacks, and observability.
  • Create architecture blueprints, sequence diagrams, and technical specifications to guide engineering teams, including designs for services that interact with large language model APIs or AI workflows.
  • Participate in code reviews, technical discussions, and sprint ceremonies to ensure architectural alignment, and use AI tools where suitable to accelerate reviews, refactoring, and documentation.
  • Design and implement messaging solutions using Apache Kafka, RabbitMQ, IBM MQ, and ActiveMQ.
  • Use Apache Camel for enterprise integration patterns, routing, and transformation pipelines, including integration with AI or large language model services where relevant.
  • Ensure high-throughput, fault-tolerant messaging architectures meet service-level agreement requirements.
  • Evaluate and recommend messaging technologies based on use case, volume, and latency requirements.
  • Develop and review production-quality Java and Spring Boot code, leading by technical example; use AI and large language model tools to assist with boilerplate, tests, and refactoring while maintaining quality.
  • Champion microservices best practices, including API design, service decomposition, and inter-service communication, including secure and observable integration with AI services.
  • Conduct and lead proof-of-concepts to evaluate new frameworks, libraries, and technologies.
  • Ensure adherence to coding standards, design patterns, and engineering best practices, including safe and responsible use of AI-generated code and suggestions.
  • Design and oversee containerized deployment strategies using Docker and Kubernetes.
  • Manage workload orchestration, autoscaling, resource quotas, and namespace design on Kubernetes clusters.
  • Collaborate with DevOps and platform teams to build robust continuous integration and continuous delivery pipelines and infrastructure-as-code practices, incorporating AI-enabled tooling to improve productivity and reliability.
  • Ensure container security, network policies, and secrets management are incorporated into the architecture.
  • Establish and embed observability frameworks covering distributed tracing, structured logging, and metrics collection.
  • Define performance monitoring and alerting standards across services and infrastructure.
  • Conduct performance profiling and tuning of Java applications, including Java Virtual Machine, heap, and garbage-collection optimization.
  • Lead performance benchmarking exercises and resolve bottlenecks in high-traffic, latency-sensitive systems.
  • Apply Java Virtual Machine memory-management expertise, including heap sizing, garbage-collection strategies, metaspace, and memory-leak analysis.
  • Use profiling tools such as JProfiler, VisualVM, and async-profiler to diagnose and resolve performance issues.
  • Tune application performance at the code, runtime, and infrastructure levels.
  • Define best practices for resource utilization and memory-efficient programming patterns.
  • Design relational data models and optimize queries for PostgreSQL, Oracle, or MySQL.
  • Architect MongoDB NoSQL solutions, including schema design, indexing strategies, and aggregation pipelines.
  • Define data access patterns, connection-pooling strategies, and caching layers.
  • Ensure data consistency, integrity, and resilience across distributed data stores.
  • Identify technology gaps and propose proof-of-concepts to validate architectural decisions before broader adoption, including AI- and large language model-based approaches where they can improve productivity, reliability, or customer outcomes.
  • Work hands-on with engineering teams during proof-of-concept phases to prototype and evaluate solutions.
  • Translate proof-of-concept outcomes into actionable architectural recommendations and implementation roadmaps.

Desired Qualifications

  • Experience in payments, financial messaging, or regulated financial technology platforms.
  • Exposure to event sourcing and stream processing, such as Kafka Streams or Apache Flink.
  • Experience with chaos engineering and resilience testing practices.
  • Hands-on experience integrating large language model APIs or using AI frameworks such as Spring AI or LangChain4j in Java-based systems.
  • Familiarity with vector databases or vector search, such as pgvector, Weaviate, Pinecone, or Milvus, and retrieval-augmented generation patterns.
  • Exposure to responsible AI practices in production, including data governance, auditability, cost and latency monitoring, and human-in-the-loop approaches where needed.

About the Company

Volante Technologies

Cloud-native PaaS for real-time payments

Volante Technologies provides cloud-native, real-time payment processing and data integration as a service for financial institutions. Its low-code platform uses visual modeling to design and manage financial messaging, payment workflows, and ISO 20022 migration, enabling real-time processing. It differentiates itself with end-to-end financial messaging and a payment hub on a cloud-native, low-code platform backed by experience serving large multinational banks. Its goal is to help banks accelerate digital transformation, migrate to modern payment standards, and securely process large-value transactions.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$111M
Headquarters
Jersey City, NJ
Founded
2001

Recently Posted Jobs

Explore more opportunities at Volante Technologies

See more jobs