Role Description 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. What you will do: - 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 Qualifications - Bachelor’s degree in computer science or related field - 1–2 years of experience in software development - 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 AI Skills/Knowledge - 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 Preferred Skills (a plus but not required) - 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 Benefits - This position is 100% remote anywhere in the US

Role Description We're looking for an AI implementer who lives and breathes AI agents. Your job is to cut through the noise of what's out there, figure out what actually works, and wire it into our business — building the agents that drive our outbound and growth, and the internal AI infrastructure the whole company runs on. - Build and connect AI agents and automations across the company - Set up outbound and growth systems: lead scraping, enrichment, and automated engagement — e.g. agents that monitor Reddit and forums for people looking to hire and engage them - Stand up a central "company memory" with specialized sub-agents that feed off it - Continuously evaluate new AI tools and frameworks, run experiments, and ship what works - Own automations end-to-end, from idea to working system Qualifications - Hands-on experience building with AI agents and automation tools (n8n, Zapier, agent frameworks, LLM APIs) - Comfortable with APIs, prompt engineering, and stitching tools together - A fast, self-directed experimenter who can cut through hype and ship - It would be great if you had business development or sales experience - Bonus: coding ability

• Design and build the core architecture for AI systems spanning multiple product areas, ensuring coherence and reuse across different applications. • Set the technical bar for the org: evaluation frameworks, testing philosophy, CI/CD for model behavior, and shared infrastructure used across multiple teams. • Identify and resolve systemic engineering gaps before they become team-wide problems — proactively, not just in response to escalations. • Take direct ownership of the hardest, most ambiguous technical problems on the team — the ones without an established playbook — and build the solution end-to-end. • Build and ship conversational agents, deep learning models, and personalization systems that require novel technical approaches. • Improve AI/ML systems and services to drive behavior change and sustained metabolic health improvements across our member base. • Raise the technical level of the team through code review and design review — this is IC technical leadership, not people management. You will not have direct reports. • Partner with product, engineering leadership, and clinical/research teams to turn ambiguous goals into technical designs you then build. • Other duties as assigned.

• Provides, guides and uses professional concepts in developing resolution to critical issues. • Train and fine-tune models using LoRA and other parameter-efficient techniques • Design, train, and evaluate multimodal models from scratch • Apply reinforcement learning techniques to model development and optimization • Experience with audio/speech ML tasks such as speaker diarization and speaker identification • Deploy, debug, and maintain distributed systems in cloud environments • Optimize inference pipelines using tools and techniques such as TensorRT, quantization, and pruning • Monitor and maintain models in production, including handling data drift and system failures • Perform data gathering, cleaning, and curation to build high-quality training and evaluation datasets • Comfortable working with a gated, continuous deployment workflow that requires unit, component, and integration tests • Applies extensive knowledge of theories, practices and design matters. • Works on issues that impact program success or addresses future concepts and products. Implementation of solutions requires a longer-term view which impacts strategic goals and objectives spanning several functions. • Exercise a wide latitude in determining objectives and approaches to critical assignments. • Knowledge of media management strategies and distribution workflows • Work closely with Product and Operations to design and optimize workflows • Apply broad expertise and knowledge in highly specialized fields or several related disciplines • Contributes to development of company objectives across and principles to achieve goals • Work on significant and unique issues where analysis of situations or data requires an evaluation of intangibles