• Build and maintain ELT pipelines and transformations in Snowflake, with a strong focus on SQL quality and performance • Develop and optimise Snowflake stored procedures / SQL-based transformations aligned to engineering standards • Work within an Azure-based ecosystem and contribute to secure, reliable pipeline operations • Design and implement Data Vault 2.0 structures (Hubs, Links, Satellites), including business vault logic where required • Re-model legacy reporting data into scalable, auditable Data Vault patterns • Collaborate with architects and domain experts to interpret and codify business rules—especially where rules differ across legacy systems • Create and maintain reporting-ready layers (e.g., information marts / dimensional patterns where appropriate) to support Power BI • Support new delivery methods such as Power Automate outputs for end users where required • Work with ingestion patterns where source data lands as Parquet (e.g., delta/Parquet structured files) • Use and support orchestration via Azure Data Factory (ADF)—especially for onboarding new sources and maintaining reliable workflows • Operate in an Agile delivery environment (e.g., Jira / Scrum), contributing to sprint planning, estimation, and continuous improvement • Participate in peer reviews and knowledge sharing to uplift capability across the team

Role Description The Data Entry Team Lead provides assistance and support for a team of Data Entry Analysts that input / duplicate medical bill information or breakdown itemization charges into a database in a timely and accurate manner while meeting production volume expectations. The Data Entry Team Lead is responsible for assisting and supporting their direct supervisor, helping to ensure the team meets protocol as well as performing supervisor duties if and when the supervisor is out. This is a remote position. - Serves as primary point of contact for Data Entry Team to handle escalations and questions - May train and coach employees on existing and new processes - Serves as a backup to the Data Entry Supervisor - Responsible for itemized data input of medical bill charges into database - Conducts detailed review by validating patient and provider information, including dates of service, bill amount and itemized bill details; verifying the information corresponds and correlates with each checked point to determine information is accurate prior and post input into database - Tracks the Company’s high priority files - Assists the supervisor as needed in training of new staff, conducting meetings, or other leadership activities as needed - Provides individual support (coaching) to all team members to ensure quotas are being met - Additional duties as assigned Qualifications - Highly effective and professional communication skills - Demonstrated leadership, high-level problem solving, and analytical skills - Ability to think and work independently, while working in an overall team environment - Proficient in Microsoft Office suite - Effectively communicate with others Requirements - High school diploma or equivalent - 1 year experience as Data Entry Analyst Benefits - Comprehensive benefits package for full-time regular employees includes: - Medical (HDHP) w/Pharmacy - Dental - Vision - Long Term Disability - Health Savings Account - Flexible Spending Account Options - Life Insurance - Accident Insurance - Critical Illness Insurance - Pre-paid Legal Insurance - Parking and Transit FSA accounts - 401K - ROTH 401K - Paid time off Company Description CERIS, a division of CorVel Corporation, a certified Great Place to Work® Company, offers incremental value, experience, and a sincere dedication to our valued partners. Through our clinical expertise and cost containment solutions, we are committed to accuracy and transparency in healthcare payments. We are a stable and growing company with a strong, supportive culture along with plenty of career advancement opportunities. We embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).

Role Description They are looking for a Senior AI Data Engineer to design and build the agentic systems powering their intelligence platform. You will work at the intersection of LLMs, financial data, and production infrastructure, creating intelligent agents that reason, plan, and execute across complex financial workflows. - Agentic Systems: Design and build single and multi-agent systems incorporating planning, memory, and tool use. - Infrastructure: Build and operate MCP servers with secure schemas and permissions. - Workflows: Develop sophisticated agentic workflows using LangGraph or equivalent frameworks. - LLM Integration: Manage prompts, structured outputs, and tool calling via SDKs. - Evaluation: Define and run LLM evaluation pipelines for quality, correctness, latency, cost, and regressions. - Observability: Build reliability infrastructure, including logging, tracing, retries, and state management. - Performance: Optimize performance and cost-efficiency from prototype to production. - Mentorship: Establish agentic best practices and mentor junior engineers. Qualifications - 5+ years of software engineering, with at least 2+ years specifically building production-level AI/ML systems. - Hands-on experience with agentic architectures, tool calling, and LangGraph (or equivalent). - Practical experience with Model Context Protocol (MCP) servers. - Demonstrated experience designing and operating LLM evaluation pipelines. - Strong Python proficiency and API design skills. - Familiarity with RAG pipelines, vector databases, and embedding-based retrieval. Requirements - Prior experience with financial data, DeFi/Crypto, or quantitative analysis. - Background in distributed systems or high-throughput data pipelines. - Active contributions to open-source AI/ML projects. Benefits - Competitive Compensation & Equity: They offer a package aligned with growth, performance, and merit. - Professional Growth: Be a foundational member of a rapidly expanding, global technology company with significant room for career advancement. - High-Stakes Impact: Work on systems that secure hundreds of billions of dollars and define the future of financial risk management. - Talent-Dense Team: Collaborate with world-class data scientists and engineers in a high-performance culture.

1.Job Summary We are looking for an AI / Machine Learning Engineer to design, develop, and deploy AI and analytics solutions using enterprise data extracted from Oracle Fusion Cloud and Oracle Databases. The role focuses on transforming Oracle business data into predictive models, insights, and decision-support tools that add real business value across Finance, HR, Sales, and Operations. The vacancy will be offshore based in favor of Samir Group - KSA 2.Key Responsibilities: Solution Design and Development Design, implement, and maintain AI/ML models (e.g., forecasting, classification, recommendation, NLP) using enterprise data sourced from Oracle Fusion and Oracle DB. Develop robust data pipelines to extract, transform, and load (ETL) data from Oracle Fusion Cloud (ERP, HCM, SCM, CX, Finance) and on-premise/cloud Oracle Databases into AI platforms and analytics environments. Build APIs, microservices, or other service layers to expose AI models to internal systems, portals, and mobile applications. Data and Model Management Perform data preparation, cleansing, and feature engineering to ensure high-quality input for AI models. Evaluate, tune, and retrain models to improve accuracy, performance, and stability. Implement monitoring, logging, and version control for models, datasets, and code. Collaboration and Governance Work closely with business stakeholders (Finance, HR, Sales, Operations, etc.) to translate business problems into AI use cases and technical specifications. Collaborate with DBAs, Oracle functional consultants, and integration teams to ensure end-to-end alignment of AI solutions with existing architecture. Ensure adherence to information security, data privacy, and regulatory requirements in all AI solutions. Documentation and Support Prepare comprehensive technical documentation, including design documents, data dictionaries, and deployment guides. Provide knowledge transfer to operations and support teams and assist in incident analysis related to AI components. 3.Qualifications (Education & Experience) Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline. A master's degree in a relevant field is an advantage. Minimum of 3–7 years of experience in software development, data science, or AI/ML engineering. Proven experience working with Oracle Database (SQL, PL/SQL, performance tuning, views, materialized views). Experience consuming or integrating data from Oracle Fusion Cloud (via REST APIs, reports, or integration tools). 4.Technical Competencies Strong programming skills in Python (preferred) and familiarity with R, Java, or similar languages. Hands-on experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Solid understanding of data modelling, relational databases, and performance optimization. Experience building and deploying RESTful APIs or microservices (e.g., Flask, FastAPI, .NET, or Java frameworks). Familiarity with cloud platforms (OCI, Azure, AWS, or GCP) for AI workloads is an advantage. Knowledge of CI/CD, Git, and DevOps practices for AI/M