Advanced Software Engineer

Relativity•Carapichaima, MA

2d•$103,000 - $155,000•Hybrid

About The Position

As an Advanced Software Engineer on the Discovery team, you will design, build, and operate the next generation of AI-driven, scalable, high-performance systems that process large volumes of data. This role combines deep technical expertise with a collaborative mindset to solve complex challenges while delivering secure, cloud-native solutions.

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field OR equivalent experience
3+ years of experience in software engineering with a focus on distributed systems
Proficiency in programming languages such as C#, Java, or Python
Experience with cloud platforms (e.g., Azure, AWS) and containerization technologies
Strong understanding of software design principles and performance optimization
Ability to work collaboratively in a team environment and communicate effectively

Nice To Haves

Experience with Elasticsearch, including index templates, ILM policies, bulk API, shard management, and cluster capacity planning
Familiarity with message-based or event streaming platforms for building high-throughput, reliable data pipelines
Experience with big data technologies such as Spark
Familiarity with CI/CD pipelines and DevOps practices
Knowledge of observability tools and best practices for system reliability

Responsibilities

Build and operate distributed search ingestion pipelines using Elasticsearch, including index lifecycle management (ILM), shard capacity planning, and rollover policies at scale across large workspace environments
Build and maintain message-based consumer services for high-volume document ingestion with robust failure handling, retry policies, and observability
Partner with architects and tech leads to implement cloud-native solutions on Azure using containerization technologies such as Docker and Kubernetes along with modern CI/CD workflows
Drive reliability improvements, including pre-flight capacity checks, error classification, and automated recovery from cluster-level failures
Contribute to team quality through pair programming, code reviews, and clear technical documentation
Champion automated testing, static analysis, observability, and DevOps practices to ensure performance and reliability
Collaborate with senior engineers and architects in design sessions and elevate team engineering practices
Use AI-assisted coding tools to accelerate development and reduce boilerplate work
Build tools and automation to streamline workflows across engineering disciplines
Collaborate with product managers and engineers to deliver high-quality features