> Markdown version of [/jobs/ext/3010371-principal-data-ml-ops-architect](https://www.wearedevelopers.com/jobs/ext/3010371-principal-data-ml-ops-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data & ML Ops Architect - **Company:** Innovative Crushing & Aggregate Inc - **Location:** Arlington, TX, United States (Remote available) - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Architectural Patterns, Automated Storage and Retrieval Systems, Audit Trail, Batch Processing, Big Data, Cloud Computing, Databases, Data Control, Information Engineering, Extract Transform Load (ETL), Data Recovery, DevOps, Distributed Data Store, Distributed Systems, Identity and Access Management, Python (Programming Language), Metadata, Operational Databases, SQL Databases, Unstructured Data, Workflow Management Systems, Privacy Controls, Scripting, Data Management, Machine Learning Operations, Automation Anywhere - **Published:** September 20, 2026 - **Apply:** https://www.careerbuilder.com/job-details/principal-data-ml-ops-architect-remote-continental-united-states-remote-arlington-va--30846672-7e96-4463-9cca-911b2a72619c ## About the Role * Deep experience architecting and owning production data platforms or distributed data systems. * Strong Python, SQL, data modeling, ETL/ELT, workflow orchestration, and cloud-data-platform experience. * Significant experience with unstructured data or document-processing systems at scale. * Strong understanding of metadata, schema evolution, lineage, provenance, data quality, observability, retries, replay, backfills, and recovery. * Experience designing systems with sensitive-data controls, governance, access management, and audit requirements. * Strong understanding of how modern AI/ML and retrieval systems depend on production data architecture. * Demonstrated technical judgment, ownership, problem solving, and ability to challenge fragile or overly complex designs. * Strong technical communication and decision-making skills. * Must be authorized to work in the United States and have lived in the US for 3 or more consecutive years. * Must be able and willing to obtain a Public Trust Clearance PREFERRED QUALIFICATIONS: * Experience in healthcare, life sciences, government, regulated industries, PHI/PII, or GDPR environments is valuable, but not required. UNAUTHORIZED USE OF AI ASSISTIVE TECHNOLOGY: All application materials must be your own original work, and interviews must be completed independently. The use of AI-generated content or AI-assisted technologies during the application or interview process is prohibited unless interviewers provide explicit permission for specific activities during a live technical assessment. Any unauthorized use of AI will result in disqualification from the hiring process., LOCATION & TELEWORKThis is a remote position following Eastern Standard Time (EST). Candidates residing in the DMV area preferred., Application Programming Interface (API), Architectural Services, Artificial Intelligence (AI), Auditing, Biology, Building Systems, Cloud Computing, Communication Skills, Customer Support/Service, Data Analysis, Data Management, Data Modeling, Data Quality, Data Recovery, Data Science, Database Extract Transform and Load (ETL), Department of Health and Human Services, DevOps, Distributed Computing, Environmental Sciences, Establish Priorities, Federal Government, Federal Laws and Regulations, Flexible Spending Accounts, Government, Healthcare, Mentoring, Metadata, Privacy Controls, Problem Solving Skills, Production Systems, Prototyping, Python Programming/Scripting Language, SQL (Structured Query Language), Small Company, Structured Data, Team Player, Technical Leadership, Technical/Engineering Design, Unstructured Data, Work From Home, Workflow Analysis ## Description We are seeking a hands-on Principal Data & ML Ops Architect to lead the architecture of our data and document-intelligence platforms. ICA works across healthcare, federal health, regulatory and life-sciences environments, building systems that turn complex structured and unstructured data into reliable, actionable intelligence. This role is responsible for designing scalable platforms that ingest, process, govern, and serve large volumes of data and documents for analytics, AI/ML, RAG, search, and operational applications. You will help modernize and unify existing platforms while establishing reusable architectural patterns for new solutions., * Architect large-scale data and document-processing platforms, from ingestion through downstream consumption. * Design robust patterns for document parsing, extraction, normalization, validation, storage, search, human review, and reprocessing. * Establish standards for schemas, metadata, lineage, provenance, data quality, reproducibility, and auditability. * Design reliable ingestion and transformation pipelines using APIs, files, batch processing, and streaming where appropriate. * Create platform patterns that enable Data Science and AI prototypes to become secure, maintainable production solutions. * Architect data and retrieval foundations supporting RAG, analytics, AI workflows, evaluation, and feedback loops. * Make architecture decisions involving scalability, reliability, security, privacy, cost, and operational complexity. * Lead technical design reviews, investigate production failures, mentor engineers, and work across Data Engineering, Data Science, DevOps/MLOps, Product, Security, and client teams. * Remain technically hands-on enough to review and develop Python, SQL, schemas, APIs, and production data pipelines. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [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 – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)