Savant is hiring a Senior Backend Engineer to join our Platform team. In this role, you will build and scale the core analytics automation platform, including orchestration, execution engines, and distributed systems infrastructure for our high-growth, AI-powered SaaS product.

What You'll Do

Develop key platform features such as job scheduling, orchestration, execution engine, and resource management.
Write clean, efficient, and well-documented code while adhering to industry standards and best practices.
Investigate and resolve issues in the platform to ensure reliability, scalability, and performance.
Work closely with cross-functional teams, including product managers and designers, to contribute to feature definitions and implementation.
Continuously improve your technical skills by working alongside experienced team members and participating in technical discussions.

What We're Looking For

Proficient in Java or similar object-oriented programming languages.
Familiarity with developing and deploying enterprise applications in cloud platforms (e.g., AWS, GCP, Azure).
Understanding of distributed systems or microservices architecture.
Strong problem-solving skills with the ability to debug and troubleshoot distributed systems issues in a cloud environment.
5+ years of experience in full-time agile software development roles.
Experience owning features end-to-end from design and development through deployment and production support.
Strong communication skills, a collaborative mindset, and enthusiasm for learning new technologies and solving complex problems.
Ownership of assigned tasks with attention to detail, a proactive approach to challenges, and a willingness to learn from and collaborate with team members.

Nice to Have

Experience with the Spring ecosystem frameworks in Java.
Experience with large-scale distributed data processing technologies like Spark and query engines like Trino.
Experience with data analytics, CI/CD pipelines, and DevOps practices.
Experience with resource management frameworks like Airflow or Argo.
Knowledge of agentic application principles, including knowledge extraction, memory design, and vector-based context management.
Experience with prompting frameworks (e.g., ReAct, CoT), multi-agent orchestration frameworks (e.g., AutoGen, CrewAI), or agent communication protocols.
Familiarity with embedding models, vector stores, and grounding techniques.