MagicOrange

Customer Success Manager

• Lead end-to-end client implementations, ensuring projects are delivered on time, on budget, and to a high standard
• Manage multiple client accounts simultaneously and balance competing priorities
• Guide clients through large-scale ITFM/TBM transformations
• Support post-implementation activities to ensure ongoing business value and ROI
• Perform detailed analysis of IT costs, consumption, and value
• Develop and present financial and operational dashboards, reports, and recommendations
• Gather client feedback to inform product improvements, service offerings, and best practices
• Engage senior stakeholders and align solutions with business drivers
• Act as a trusted advisor and identify opportunities to drive client success and platform adoption
• Escalate and resolve complex client issues with strategic guidance
• Collaborate with the Customer Success team to track progress and provide actionable insights
• Mentor and coach junior consultants
• Facilitate workshops, trainings, and knowledge-transfer sessions for client teams

Full-stack Engineer

• Working across the MagicOrange Tech stack, develop performant, robust, secure and maintainable software solutions using modern, industry-standard best practices and principles.
• Within a team environment, proactively analyze , clarify, code and unit test software, including features, defects and refactoring
• Review existing delivery dates and work requirements with current knowledge set, analyze possible alternatives and communicate options and their affects , both technical and upon delivery date
• Participate in code reviews, both of your own code and as a reviewer
• Participate in project teams to create working software
• Record and report status in an agile environment
• Contribute ideas to planning, refinement and estimation and occasionally mentor other engineers
• Identify, design, and implement internal process improvements: automating manual processes, optimizing for delivery, re-designing infrastructure for greater scalability, etc.
• Design, build, and maintain AI agentic systems: orchestrate multi-step autonomous workflows, integrate LLMs via API, and implement tool-use, memory, and reasoning patterns that solve real business problems.
• Apply prompt engineering best practices, evaluate and iterate on model outputs, and embed responsible-AI principles including safety guardrails, output validation, and human-in-the-loop checkpoints.
• Stay current with the rapidly evolving AI landscape, evaluating new models, frameworks, and agentic patterns, and champion their adoption where they deliver measurable product or operational value.

Senior Software Developer

Cloud Engineer

• Optimize and enhance existing data pipelines, ETL processes, and data workflows to improve performance, scalability and reliability.
• Implement best practices for data processing, storage, and retrieval.
• Implement automated testing within Databricks using frameworks such as pytest and nutter: write unit tests for notebooks and PySpark transformations, integration tests across pipeline stages, and data quality assertions, with results surfaced through CI/CD pipelines.
• Design, implement and maintain algorithms to solve technical problems related to data processing and analytics.
• Collaborate with data scientists to support and optimize machine learning algorithms and models in production.
• Assist to benchmark and ensure efficient use of computational resources for data processing and algorithm execution.
• Design and implement AI agentic workflows that automate multi-step data tasks: orchestrate LLM-powered agents to perform data discovery, anomaly investigation, and automated root-cause analysis within the data platform.
• Apply prompt engineering and model evaluation practices when integrating large language models into data pipelines; enforce responsible-AI guardrails including output validation and human-in-the-loop review for high-impact decisions.
• Design, implement and maintain solutions for data integration from various sources, ensuring data consistency and integrity.
• Work on data ingestion and transformation processes to support analytics and reporting needs.
• Validate integrated data using Databricks-native testing approaches: apply Delta Live Tables expectations, Great Expectations, or equivalent data quality frameworks to enforce schema, completeness, and accuracy contracts at ingestion.
• Work closely with the technical product owner to understand business requirements and translate them into technical solutions.
• Provide technical support and guidance to other team members regarding data-related issues.
• Work closely with cross-functional teams to understand data requirements and deliver solutions that meet business needs.
• Help to document key processes and services for the purposes of sharing the load and approach to technical support related issues.
• Work in conjunction with the BI Engineering to develop and maintain both product and internal dashboards and reports.
• Interpret data to provide meaningful insights and recommendations to stakeholders.
• Work closely with business teams to understand their and customer reporting needs and deliver tailored solutions.
• Ensure data accuracy and integrity in all reports and dashboards.

Customer Success Manager

Senior Software Developer

Cloud and Data Engineer