Senior Software Engineer (Elasticsearch, Scala)

We are looking for a Senior Software Engineer (Elasticsearch, Scala) to join a team powering food search and logging for one of the world’s leading health and nutrition platforms. You’ll contribute directly to the systems that drive search — backend services, search infrastructure, and experimentation — with a focus on improving core metrics: conversion rates, time to log, query abandonment, and result relevance.

What you’ll do

• Contribute to, build, and maintain backend services that drive the food search experience, integrating with systems across the broader engineering organization.
• Perform search performance tuning end-to-end — data design, indexing, query evaluation, and iterative improvement within Elasticsearch.
• Assist in the evaluation and implementation of search and data technologies that improve result quality and user experience.
• Collaborate closely with senior search engineers, product management, and leadership on solution discovery, experiment planning, and delivery.
• Contribute to the development of tools, processes, and metrics for measuring and monitoring search quality.

Required skills & experience

Elasticsearch

• Demonstrated experience with performance tuning, query analysis, and relevance optimization in Elasticsearch at scale.
• Strong understanding of index design, mapping strategies, cluster management, and scoring/ranking mechanics.
• Familiarity with high availability, disaster recovery, and operational monitoring for Elasticsearch clusters.
• Ability to deploy new indexes or clusters as needed for load balancing or experimentation.
• Ability to translate product specifications into technical requirements and deploy ranking and relevance experiments with clearly defined success criteria and metrics.

Scala

• Strong experience writing, shipping, and maintaining Scala services in production.
• Comfortable working across a stack that also includes SQL and Python — Scala is the primary language for this engagement.

Agentic development

• Active user of AI development tools such as Claude Code, Cursor, or comparable AI-powered coding environments — shipping production code with them, not just using autocomplete.
• Familiarity with agentic coding patterns and workflows — code generation, refactoring, debugging, and test authoring.
• Able to articulate how AI tooling fits into their development process and where human judgment remains critical.

Engineering fundamentals

• First-hand experience building, scaling, and supporting large-scale data infrastructure systems in production.
• Strong understanding of database design, data architecture, and performance tuning across multiple data stores — MySQL, MongoDB, DynamoDB, Redis, or similar.
• Experience with high-volume messaging systems such as Kafka.
• Familiarity with AWS, GCP, or other cloud platforms.
• Strong peer code review practices.

Preferred qualifications

• Experience leveraging AI workflows for meaningful development acceleration beyond autocomplete — code generation, refactoring, debugging, and test authoring at scale.