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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Everforth Apex - **Location:** Greenwood Village, CO, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon S3, Automation of Tests, Bash Shell, Big Data, Computer Programming, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Network Architecture, Object-Oriented Software Development, Shell Script, Simple Network Management Protocols, Software Engineering, SQL Databases, Workflow Management Systems, Datadog, Computer Network Operations, Large Language Models, Multi-Agent Systems, Prompt Engineering, Boto3, Gitlab, Git, Data Lakes, Information Technology, Deployment Automation, Restful APIs, Software Version Control - **Published:** September 26, 2026 - **Apply:** https://www.dice.com/job-detail/9f9dd888-9e62-4a33-8c5e-5f50d91b8697 ## About the Role Education: Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related field, or equivalent relevant experience., * Bachelor's degree: 5+ years of relevant data science, machine learning, or agent/software development experience. * Master's degree: 3+ years of relevant data science, machine learning, or agent/software development experience. * Strong experience building and evaluating AI agents with tools like LangSmith. * Strong Machine Learning background, as agents run on models and their outputs. Technical Skills: * Strong software engineering fundamentals, particularly object-oriented programming. * Programming experience with Python and/or Scala, and an openness to learning new coding technologies. * Bash or Shell scripting experience. * Experience building AI agents programmatically from the ground up using code-based frameworks (e.g., LangGraph). * Basic understanding of large language models and agentic patterns (e.g., multi-step reasoning, tool/function calling). * Experience with prompt engineering and context engineering. * Demonstrated experience evaluating model or agent output quality, including designing evaluation datasets. * Experience deploying solutions to production, with an understanding of version control and automated testing. * Experience with AWS services (e.g., S3, Athena, SageMaker) and working with Big Data. * Strong understanding of SQL and working with structured/tabular data. * Experience with Git-based version control and collaborative development workflows. * Basic understanding of network infrastructure., * Experience with agent evaluation and tracing/observability platforms (e.g., LangSmith). * Experience integrating agents with external tools and data sources. * Experience deploying agents through CI/CD pipelines (e.g., GitLab). * Familiarity with LLM-as-a-judge metrics and understanding when supervised, gold-standard evaluation is required. * Experience in the telecommunications industry or other large-scale network operations environments. * Familiarity with network data sources such as telemetry, syslogs, SNMP traps, and device configuration data. * Experience with workflow orchestration tools for event-driven agent execution. * Experience with REST APIs and cloud SDKs (e.g., boto3). ## Description * Design, build, and maintain AI agents programmatically using code-based agent frameworks, with explicit control over agent state, control flow, tool integration, and prompt behavior. * Develop, enhance, and maintain agents across the portfolio as they evolve with business needs, including investigation, recommendation, data lake exploration, and conversational agents. * Integrate agents with upstream data and tooling, including anomaly detection model outputs, historical and processed data, and real-time sources. * Deploy agents to production through the established CI/CD pipeline, coordinating with engineering teams on containerization, gateway integration, and deployment automation. * Design and execute project-specific, supervised evaluation of agent quality by constructing gold-standard datasets with subject matter experts. * Instrument and analyze agent behavior using tracing and observability tooling to diagnose failures and drive iterative improvement. * Apply prompt engineering, context engineering, and tool design to improve agent reasoning, accuracy, and reliability. * Ensure agents are built to production standards: version-controlled, testable, and with deterministic, reviewable control flow. * Collaborate with Data Engineering, Anomaly Detection, and Platform Engineering teams. * Support the extension of agent capabilities toward autonomous remediation use cases. * Document agent designs, evaluation methodologies, and results for varied technical audiences. ## Related Videos - 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[Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)