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Operations Quality Principal
Cynet SystemsIndianapolis, IN🇺🇸United StatesPosted 5 Aug 2026
Quick Overview
Salary
$64 - $67/hr
Work Type
Hybrid
Level
Leader
Job Description
We are looking for Operations Quality Principal for our client in Indianapolis IN.
Job Title: Operations Quality Principal
Job Location: Indianapolis IN
Job Type: Contract
Job Overview:
Pay Range $64hr - $67hr
Requirement/Must Have:
- 5-7+ years of experience building and deploying machine learning algorithms, complex data models, or automated software tools to support enterprise-level decision-making.
- Strong hands-on engineering proficiency with enterprise data science environments (such as Dataiku or ML Studio).
- Advanced understanding of NLP, LLMs, and prompt engineering architectures.
- Strong proficiency in core programming for data modeling (Python, SQL) and developer workflows (Git, Jira, Confluence, and script automation environments).
- Solid structural knowledge of cloud data warehousing (Snowflake), pipeline concepts (AWS), and business intelligence delivery tools (ThoughtSpot, Tableau).
- Experience working within a highly regulated manufacturing environment (such as Pharma, Diagnostics, or Medical Devices).
- Sound understanding of GxP compliance, US FDA 21 CFR Part 820 Quality Management System Regulations, and ISO 13485/9001 standards.
- Proven capability acting as a principal technical leader, driving global cross-functional projects, and aligning stakeholder expectations with a team-first, agile mindset.
Responsibilities:
- Design, scale, and deploy robust machine learning and NLP pipelines utilizing approved enterprise data platforms, primarily focusing on Dataiku and Azure ML Studio layers.
- Evaluate and deploy advanced AI solutions. Utilize the Claude Agent SDK or comparable approved SDKs as targeted implementation options for complex use cases that genuinely require custom, automated agents to navigate cross-system data silos.
- Architect and mature our global AI Use-Case Backlog. Guide the deployment of Natural Language Processing (NLP) and Large Language Models (LLMs) to automate initial sorting, risk-grading, and real-time categorization of complex quality data.
- Oversee the conceptual data modeling and integration pipelines feeding into core analytics repositories (such as Snowflake and AWS). Partner with builders to translate complex datasets into high-performing enterprise business intelligence views.
- Assume formal Product Owner and architectural design oversight for core Quality Insight platforms, dashboards, and automation frameworks.
- Establish and champion clean repository management, version control, and collaborative code review practices via Git. Drive standardized automation workflows utilizing Jira and Confluence to optimize the subchapter's intake pipeline and eliminate communication latency.
- Ensure all deployed AI models, automated scripts, and data pipelines adhere to computerized system validation protocols under GxP, US FDA (21 CFR Part 820), and ISO 13485 standards. Guide the team in authoring, reviewing, and executing technical validation documentation for data integrity.
- Partner directly with Quality Site Heads, Business Leaders, and global cross-functional squads to break down organizational data silos and resolve systemic reporting barriers across site networks.
- Establish, champion, and mentor an Operations Quality Community of Practice for Quality AI & Data Insights. Elevate organizational digital fluency by coaching other team members on best practices.
- Maintain a 95%+ alignment between automated AI/analytical insights and manual audit findings, fully meeting software validation protocols.
- Drastically reduce the cycle time required to compile and generate monthly and quarterly quality reports across the global network via automated data assembly.
- Secure high active usage metrics for all owned enterprise data products, capturing measurable efficiency savings.
Skills:
- Strong verbal and written communication skills.
- Excellent communication and presentation skills.
- Ability to communicate effectively with stakeholders.
Education and Experience:
- Bachelor's, Master's, or Ph.D. degree in Data Science, Informatics, Data Analytics, Computer Science, or a related technical field.
- Hands-on experience or deep conceptual understanding of custom agent architectures utilizing tools like the Claude Agent SDK or comparable enterprise-approved development kits.
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Benefits
Our Benefits Include:
- Medical, Dental, and Vision Insurance
- 401(k) Retirement Plan
- Health Savings Account (HSA)
- Disability Insurance (Short-Term and Long-Term)
- Life and AD&D Insurance
- Paid Sick Leave (where required by applicable state or local law)
- Supplemental Insurance Plans
- Identity Theft Protection
- Pet Insurance
- Employee Wellness Programs
- Employee Assistance Program (EAP)
- Career Growth and Professional Development Opportunities
Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws.
About Cynet Systems
Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia.
As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
Skills
SQL
AWS
Machine Learning
NLP
SOC 2
Snowflake
Tableau
Agile
Assembly
Azure
Compliance
Confluence
Customer Success
Git
Jira
Python
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