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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Software Engineer - AI - **Company:** LogicMonitor, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $143,000.0 - $198,440.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Computer Programming, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Distributed Data Store, Fault Tolerance, Python (Programming Language), Operational Data Store, Role-Based Access Control, Redis, Search Technologies, Data Streaming, Unstructured Data, WebSocket, Data Logging, Data Ingestion, Large Language Models, Apache Spark, Spring-boot, Backend, Fastapi, Build Management, Containerization, Data Lakes, AI Platforms, Kubernetes, Information Technology, Data Lineage, Apache Kafka, Live Streaming, Machine Learning Operations, Vertica, Data Pipelines, Automation Anywhere, Microservices - **Published:** July 1, 2026 - **Apply:** https://dejobs.org/x/x/28AEA3370045465582216ABD659CE627/job/ ## About the Role * Bachelor's degree in Computer Science, Data Engineering, or a related field. * 4-5 years of experience in backend or data systems engineering. * Experience building streaming data pipelines (Kafka / Spark or any similar technology). * Strong programming background in Java and Python, including microservice design. * Experience with ETL, data modeling, and distributed storage systems. * Familiarity with LLM pipelines, embeddings, and vector retrieval. * Understanding of Kubernetes, containerization, and CI/CD workflows. * Awareness of data governance, validation, and lineage best practices. * Strong communication and collaboration across AI, Data, and Platform teams., At this time, we are able to consider candidates who are authorized to work in the United States on a full-time, permanent basis without requiring new or initial employer-sponsored work authorization. Candidates who currently hold valid U.S. work authorization that can be transferred to a new employer (such as certain H-1B statuses) may be considered on a case-by-case basis. ## Description * Design and build streaming and batch data pipelines that process metrics, logs, and events for AI workflows. * Develop ETL and feature-extraction pipelines using Python and Java microservices. * Integrate data ingestion and enrichment from multiple observability sources into AI-ready formats. * Build resilient data orchestration using Kafka, Airflow, and Redis Streams. * Develop data indexing and semantic search for large-scale observability and operational data. * Work with structured and unstructured data lakes and warehouses (Delta Lake, Iceberg, ClickHouse). * Collaborate with the AI Platform team to manage embeddings, metadata, and model context storage. * Optimize latency and throughput for retrieval, query expansion, and AI response generation. * Build and maintain Java microservices (Spring Boot) that serve AI and analytics data to Edwin and AIOps applications. * Develop Python APIs (FastAPI / LangGraph) for LLM orchestration, summarization, and correlation reasoning. * Implement schema contracts and streaming protocols (REST, gRPC, SSE, WebSockets) between services. * Ensure fault-tolerant, observable, and performant API infrastructure. * Instrument services with OpenTelemetry for unified metrics, tracing, and logging. * Implement data validation, schema evolution, and lineage tracking across AI pipelines. * Enforce data privacy, RBAC, and compliance for model inputs and stored context. * Collaborate with SRE and AI teams to monitor and optimize end-to-end AI system performance. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [You are not an AI developer](https://www.wearedevelopers.com/videos/1148-you-are-not-an-ai-developer) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Accelerating Authentication Architecture: Taking Passwordless to the Next Level](https://www.wearedevelopers.com/videos/733-accelerating-authentication-architecture-taking-passwordless-to-the-next-level) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)