Workiva’s Search Team powers how customers find and interact with information across our platform. As a Senior Software Engineer on this team, you’ll design and build backend services in Java on top of OpenSearch, enabling everything from full-text document search to semantic and natural language search to support our Generative AI initiatives. You’ll take ownership of projects, collaborate in a highly interactive and supportive remote environment, and help shape the future of intelligent search at Workiva. What You’ll Do - Design, build, and scale backend services in Java, integrated with OpenSearch - Develop indexing strategies, schema mappings, and optimized query patterns for large datasets - Support Workiva’s GenAI and RAG endpoints, enabling semantic and natural language search features - Leverage AWS cloud infrastructure and Kafka event streaming for scalable systems - Monitor, tune, and debug search infrastructure for performance, reliability, and accuracy - Partner with cross-functional teams to deliver search-driven features that meet customer needs - Provide mentorship through code reviews, technical guidance, and collaboration - Lead well-scoped projects, define milestones, and improve team processes What You’ll Need Minimum Qualifications - Bachelor's degree in Computer Science, Engineering or a related technical field - 2+ years of experience in software development or related field Preferred Qualifications - Proficiency in Java or another JVM language (e.g., Scala, Kotlin) - Experience with search engines such as OpenSearch, Elasticsearch, or Solr - Strong understanding of indexing, query optimization, and distributed search performance - Hands-on experience designing and scaling backend services in a cloud environment (AWS preferred) - Kafka or other event streaming experience - Familiarity with semantic search, embeddings, or NLP techniques - Exposure to AI/ML concepts, particularly around ranking or search relevance - Strong collaboration and communication skills in a remote-first, video-driven culture Working Conditions & Travel Requirements - Minimal (<10%) travel for team jams or engineering wide conferences - Reliable internet access for remote working opportunities How You’ll Be Rewarded ✅ Salary range in the US: $111,000.00 - $178,000.00✅ A discretionary bonus typically paid annually ✅ Restricted Stock Units granted at time of hire ✅ 401(k) match and comprehensive employee benefits package The salary range represents the low and high end of the salary range for this job in the US. Minimums and maximums may vary based on location. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience and other relevant factors. Employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other protected characteristic. Workiva is committed to working with and providing reasonable accommodations to applicants with disabilities. To request assistance with the application process, please email talentacquisition@workiva.com. Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards. Workiva supports employees in working where they work best - either from an office or remotely from any location within their country of employment. #LI-MJ2

• Pragmatically executing on strategic initiatives • Collaborating cross-functionally to plan, design, and execute on strategic priorities • Creating a technical roadmap and resource plan • Growing the team with a high hiring bar, and onboarding new team members • Growing people through formal and informal feedback and career growth plans • Building a strong team culture • Contributing to business strategy with an engineering perspective • Implementing processes and technologies that optimize velocity, including AI tools

• Build and maintain robust data pipelines that ingest, transform, and validate complex customer data using PySpark, Python, and dbt to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use. • Help improve integrations with new customers, making the process faster and more repeatable through thoughtful tooling. • Contribute to the adoption of cutting-edge AI tooling (e.g., LLM-assisted data cleaning, semantic validation, and anomaly detection). • Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features. • Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations. • Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need. • Learn and grow by pairing with other engineers, participating in design reviews, and taking on bigger and bigger projects.

Afresh is the leading AI company in fresh food—partnering with grocers like Albertsons, Wakefern, Meijer, and Stater Bros to order billions of dollars of fresh food in over 12,000 grocery departments nationwide. Following record-breaking 70% growth in 2025, we’ve expanded our platform to cover all fresh departments, launched our full store suite, and debuted DC Fresh Buying. We’re on a mission to eliminate food waste and make fresh food accessible to all. In 2025 alone our software helped save 200M lbs of food waste. If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines the future of fresh, there is no better time to join us. About the Role We’re looking for a Data Engineer who’s excited to work at the intersection of food waste, large-scale data processing, and applied AI. In this role, you’ll help shape how customer data flows through our platform, improving how we ingest, transform, and operationalize real-world datasets to drive down food waste for grocery chains. You’ll work closely with other data engineers, product engineers, and AI/ML engineers to design and implement reliable, efficient ETL pipelines and streamline how we integrate with new customers. You’ll contribute to the development of new features that support our expanding product lines. Your work will have a direct and visible impact on our ability to onboard customers more easily/quickly and power our machine learning grocery solution. What You’ll Do - Build and maintain robust data pipelines that ingest, transform, and validate complex customer data using PySpark, Python, and dbt to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use. - Help improve integrations with new customers, making the process faster and more repeatable through thoughtful tooling. - Contribute to the adoption of cutting-edge AI tooling (e.g., LLM-assisted data cleaning, semantic validation, and anomaly detection). - Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features. - Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations. - Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need. - Learn and grow by pairing with other engineers, participating in design reviews, and taking on bigger and bigger projects. Skills and Experience - 2+ years of experience building ETLs or data workflows with Python, PySpark, SQL, or similar tools. - Comfortable working with messy, incomplete, or inconsistent datasets—and turning them into something structured and usable. - Experience in identifying areas where tooling or automation can simplify workflows and reduce manual effort. - Experience or strong interest in platforms like Databricks, Snowflake, and dbt. - Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions. - Attention to detail and pride in delivering robust, maintainable solutions. - Collaborative and communicative — you work well across teams and aren't afraid to ask questions. - Learning mindset — hungry to grow your skills and move fast. We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification. We encourage you to apply even if you don’t meet every requirement. This position is not eligible for employer sponsorship Salary Band in Canada: $114,00 - 154,000 About Afresh Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices. Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals including ICML, and we've raised over $148 million in funding from investors including former co-CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors. Fresh is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility. Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law. Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.