
51 - 200 employees
Founded 1991
🛡️ Insurance
💳 Fintech
Insurance • Software • Fintech
Bond-Pro is a leading provider of automation software products specifically designed for Surety professionals, including insurance carriers and agencies. With over 30 years of experience, Bond-Pro focuses on enhancing Surety technology through a comprehensive management and automation platform that enables clients to improve underwriting efficiency, expedite bond issuance, and lower operating costs. Their fully integrated software suite revolutionizes the Surety industry by streamlining account management and ensuring efficient lifecycle management of Surety bonds.
🔥 0 minutes ago
AWS
Azure
Cloud
Google Cloud Platform
Hadoop
Java
JavaScript
Kafka
Kotlin
Kubernetes
Microservices
Node.js
NoSQL
Python
Rust
Scala
Spark
SQL
TypeScript
Go
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51 - 200 employees
Founded 1991
🛡️ Insurance
💳 Fintech
Insurance • Software • Fintech
Bond-Pro is a leading provider of automation software products specifically designed for Surety professionals, including insurance carriers and agencies. With over 30 years of experience, Bond-Pro focuses on enhancing Surety technology through a comprehensive management and automation platform that enables clients to improve underwriting efficiency, expedite bond issuance, and lower operating costs. Their fully integrated software suite revolutionizes the Surety industry by streamlining account management and ensuring efficient lifecycle management of Surety bonds.
• Operate independently within an Agile team and take ambiguous requirements from concept to production • Participate in the full Scrum/Agile sprint cycle, including backlog refinement, sprint planning, capacity estimation, daily standups, sprint review, and retrospectives • Participate in requirement refinement sessions with product owners and stakeholders, turning ambiguous requests into well-scoped, estimable stories • Apply modern software design patterns and enforce separation of concerns across the codebase • Design and build proofs of concept to validate new approaches before full implementation • Integrate AI/ML and/or NLP components into production systems • Design and implement systems handling structured, semi-structured, unstructured, and schema-bound data formats, including CSV, relational data, JSON, and Avro • Contribute to big data architecture and design patterns, including batch and/or streaming pipelines, data partitioning, and scalable processing approaches • Collaborate with UI/UX on interface design decisions, aligning frontend implementation with usability and design intent • Mentor junior developers through code review, pairing, and design discussions • Bring architectural judgment to structuring and processing data at scale
• Proven experience working in Scrum/Agile teams, including sprint planning, capacity estimation, and iterative delivery • Strong grasp of modern design patterns, including strategy, factory, repository, and observer, and separation of concerns • Experience with UI/UX collaboration and requirement refinement • Hands-on experience with structured, semi-structured, unstructured, and schema-based data formats, including CSV, JSON, and Avro • Big data technology experience, such as Spark, Kafka, Hadoop ecosystem, or equivalent • Demonstrated experience building and validating proofs of concept (POCs) • Experience designing and building microservices architectures, including service decomposition, inter-service communication, API contracts, and independent deployability • Strong understanding of data layer and persistence design patterns, including repository pattern, unit of work, CQRS, data access layer abstraction, ORM versus raw query tradeoffs, caching strategies, and relational SQL and NoSQL database design • Experience with cloud platforms, including AWS, Azure, or Google Cloud Platform, with core compute, storage, and managed data services on at least one major provider • Applied experience with Machine Learning, NLP, or AI, integrating AI/ML components into production systems • Proficiency in one or more modern languages beyond the primary stack, such as Python, Scala, Go, Java, Kotlin, Rust, TypeScript/Node.js, or C# • Multi-cloud exposure across AWS, Azure, and GCP, and familiarity with cloud-native patterns such as containers, Kubernetes, serverless, and managed data/streaming services
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