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Software Engineer, Backend - AI Practice Team
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Software Engineer, Backend - AI Practice Team
- United States
- United States
À propos
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. 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. This role reports to a project manager and does not initially include direct reports. $90,000 - $150,000 USD Starting salary is based on multiple factors including skillset and experience. Notice: This role has been opened for a future need expected within three months of the original posting date of this position. Potential candidates may not receive communication until the open headcount is confirmed.
Compétences linguistiques
- English
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