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Mid-level AI/backend role, metro location and broad specialized skillset create high candidate density.
Specialized ML/AI platform and LLM pipeline expertise reduces cross-industry transferability.
Explicit 4-5 years plus mandatory Java/Python, streaming, and LLM pipeline skills make shortlisting highly strict.
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Design and build scalable streaming and batch data pipelines, ETL processes, and microservices to support AI-driven observability and AIOps products.
Develop and maintain APIs and data infrastructure to enable real-time, explainable AI insights including data indexing, semantic search, and retrieval frameworks.
Collaborate with AI Platform, SRE, and Data teams to optimize AI system performance, ensure data compliance, and deliver reliable AI-powered digital infrastructure visibility.
Bachelor’s degree in Computer Science, Data Engineering, or related field.
4-5 years of experience in backend or data systems engineering.
Strong programming skills in Java and Python with experience in microservice design.
Experience with streaming data pipelines (Kafka/Spark or similar), ETL, distributed storage systems, and familiarity with Kubernetes and CI/CD.
Experienced in building large-scale data pipelines and APIs for AI and observability platforms with focus on reliability and latency optimization.
Comfortable working at the intersection of backend systems, data engineering, and AI, including knowledge of LLM pipelines, embeddings, and vector retrieval.
Able to collaborate across multidisciplinary teams (AI, Data, SRE) to deliver robust, compliant, and performant AI infrastructure.