Associate Software Engineer – Java (AI First)

Precisely US Jobs

1d•Remote

About The Position

Precisely is the leader in data integrity. We empower businesses to make more confident decisions based on trusted data through a unique combination of software, data enrichment products and strategic services. Precisely is an AI-first organization. All employees are expected to demonstrate proficiency in applying AI tools to accelerate their work, improve output quality, and eliminate low-value tasks. Candidates should be comfortable using generative AI tools (e.g., Microsoft Copilot, ChatGPT) in their day-to-day workflows, able to evaluate AI-generated outputs critically, and open to continuously adopting new AI capabilities as they emerge. We are seeking an enthusiastic and motivated Associate Software Engineer to join our Master Data Management (MDM) product line within Precisely’s Data Integrity Suite. In this role, you will help build the backend systems that support Precisely’s next-generation MDM platform. You will work on enterprise-grade applications using Java, Python, and Angular to develop APIs, services, and data layers that manage trusted, high-quality enterprise data across integrations, workflows, and analytics. As part of an AI-first engineering organization, you will use AI tools as a core part of designing, building, testing, and operating software. You will be expected to apply AI to accelerate development, improve code quality, and strengthen problem-solving. You will work closely with engineers, architects, and product teams to deliver scalable, reliable, production-ready backend capabilities that address real customer needs.

Requirements

Bachelor’s degree in computer science or related field
1–2 years of experience in software development
Java
Strong understanding of Java and object-oriented programming
Understanding of API design and application architecture
Basic knowledge of relational or NoSQL databases (SQL Server, Oracle, MongoDB, etc.)
Test-driven development mindset with understanding of unit test patterns, mocking strategies, and test quality gates
Understanding of concurrent programming fundamentals, including thread-safety contracts, immutability, and shared state management
Familiarity with async/reactive patterns (CompletableFuture, async services, event-driven workflows)
Strong problem-solving and communication skills
Hands-on experience using AI tools for coding, debugging, and productivity (Copilot, Claude, ChatGPT, etc.)
Ability to evaluate and validate AI-generated code for correctness and performance
Interest in applying AI to data platforms, APIs, and backend workflows
Eagerness to adopt AI-assisted development practices as part of daily work

Nice To Haves

Experience with Spring Boot, Hibernate, or microservices architecture
Exposure to cloud platforms (AWS, Azure) and distributed systems
Database knowledge (SQL/NoSQL)
Understanding of data platforms, MDM concepts, or data integration pipelines
Basic frontend awareness
Structured logging and observability (SLF4J, Logback, MDC context, correlation IDs, Datadog integration)
Event-driven architecture patterns, messaging standards (CloudEvents, async workflows, dead-letter routing)
Data mapping patterns and DTO design
ORM and query optimization (Hibernate, fetch strategies, lazy loading, pagination, N+1 query avoidance)
Defensive programming practices (null safety, input validation, guard clauses, failure atomicity)
Basic knowledge of Python or AI/ML concepts
Familiarity with CI/CD pipelines and DevOps practices

Responsibilities

Design, develop, and maintain backend services using Java, Spring Boot, and REST APIs
Contribute to data models, API contracts, and service integrations for MDM workflows
Build systems supporting data ingestion, transformation, governance, and integration pipelines (aligned to MDM/DI ecosystem)
Use AI-powered tools to accelerate coding, debugging, testing, and design workflows
Implement clean architecture patterns (controller, service, repository) with strong separation of concerns
Implement structured logging and observability patterns (SLF4J, MDC context, correlation IDs) to enable production debugging and monitoring
Write high-quality unit and integration tests with proper mocking strategies to ensure code quality and maintainability
Debug and optimize performance, scalability, and reliability of backend systems
Apply observability best practices (logging, tracing, correlation IDs) to support production monitoring
Participate in Agile ceremonies, code reviews, and CI/CD practices
Collaborate cross-functionally with frontend, QA, product, and platform teams
Continuously learn and evaluate new technologies, especially in AI/agentic workflows and backend platforms