Software Engineer, Backend - AI Practice Team

ABS is seeking an exceptional Backend Engineer to join us full-time on our Artificial Intelligence (AI) Practice Team. In this role, you will design and scale high-performance backend systems that power real-time analytics and retrieval-augmented generation (RAG) pipelines. You’ll build distributed services that deliver sub-500ms response times under high load, enabling next-generation AI and data-driven applications.

Location:

This position can be based in Houston, Texas; Knoxville, Tennessee; or Washington, DC.

What You Will Do:

• Architect distributed systems: Design and implement event-driven backends using advanced patterns such as CQRS, Event Sourcing, Saga, and Circuit Breakers.Build at scale: Develop and maintain web services in Go and Python, leveraging cloud-native infrastructure for resiliency and elasticity.
• Optimize for performance: Ensure APIs and data pipelines meet strict SLAs through advanced performance profiling, caching, and query optimization.
• Stream real-time data: Engineer high-throughput pipelines using Apache Kafka and other event streaming platforms.
• Deliver reliability: Establish strong observability, testing, and monitoring practices to guarantee consistency, uptime, and fault tolerance.

What You Will Need:

Education and Experience

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 8+ years of backend development experience, with a focus on high-performance, data-intensive systems.
• 5+ years deploying and operating applications on AWS, Azure, or Google Cloud.
• Proven track record building production systems that sustain high concurrency and throughput.

Knowledge, Skills, and Abilities

• Expert proficiency in Go and Python for backend development.
• Deep experience with event-driven architectures and real-time streaming, particularly Apache Kafka.
• Mastery of distributed system patterns (CQRS, Event Sourcing, Saga, Circuit Breaker, Bulkhead).
• Strong command of performance optimization—caching layers, database tuning, and system-level profiling.
• Hands-on experience with analytics platforms (e.g., Databricks) for large-scale data processing and ML workflows.
• Proficiency with containerization (Docker, Kubernetes) and infrastructure as code.
• Familiarity with vector databases, search systems, and advanced retrieval-optimized data structures.

Reporting Relationships:

This role reports to a project manager and does not initially include direct reports.

Salary Range:

$90,000 - $150,000 USD

Starting salary is based on multiple factors including skillset and experience.