Senior AI/Data Engineer, Data Platforms, Machine Learning, Applied AI

Intertwine Associates

. Architect and lead delivery of enterprise data platforms and pipelines on Azure or equivalent cloud services .

Posted 9/30/2026full-timeRemote • United StatesSenior💰 $130,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in architecting and delivering enterprise data platforms and machine learning solutions on Azure, with a strong focus on data governance, compliance, and MLOps practices. Proven ability to lead technical teams, mentor engineers, and communicate effectively with diverse stakeholders.

Highest-signal resume keywords

Expert Python ProgrammingAdvanced SQLAzure Data Services ExperienceMLOps Practices ImplementationMachine Learning Systems Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DevelopmentMachine Learning Application DesignETL Design and ImplementationAPI and Microservices DevelopmentData Validation and Quality AssuranceLarge Language Model ApplicationsRetrieval-Augmented GenerationProduction Experience with PyTorchProduction Experience with TensorFlowProduction Experience with scikit-learn

Soft Skills

Excellent Written CommunicationExcellent Verbal CommunicationMentoring and Leadership

Tools & Technologies

DatabricksSnowflakeMicrosoft FabricAzure Machine LearningContainers

Certifications & Qualifications

Microsoft Azure CertificationsAWS CertificationsGoogle Cloud Certifications

Industry Keywords

Data GovernanceComplianceNIST AI Risk Management FrameworkFedRAMPFISMAFederal Data Security Requirements

Tech Stack

Tools & technologies

AWSAzureCloudETLMicroservicesNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Architect and lead delivery of enterprise data platforms and pipelines on Azure or equivalent cloud services
Set standards for ETL design, schema enforcement, data validation, quality checks, and data lineage
Review other engineers' work against established standards
Design, build, and deploy machine learning and AI solutions, including large language model applications, retrieval-augmented generation, document understanding, and agentic workflows
Implement evaluation and guardrails for AI solutions
Build secure API endpoints and microservices for analytics and ML platforms
Establish MLOps practices including experiment tracking, model registries, CI/CD, containers, monitoring, and cost and performance tuning
Apply data and AI governance for compliance, reproducibility, auditability, and responsible AI
Apply federal frameworks such as the NIST AI Risk Management Framework
Translate mission and business needs into technical roadmaps, estimates, and client leadership briefings
Work directly with client program leadership, architects, data scientists, and governance teams
Advise on technical direction and represent Intertwine Associates and clients professionally
Mentor engineers and data scientists
Lead technical work across multidisciplinary teams

Requirements

What you’ll need

7+ years of experience building data pipelines, machine learning systems, or AI applications in production
2+ years leading technical work
Expert Python, including Pandas and NumPy
Advanced SQL
Experience integrating relational and unstructured data sources
Deep hands-on experience with Azure data services, or equivalent AWS or Google Cloud experience
Production experience with PyTorch, TensorFlow, or scikit-learn
Experience with data validation, schema enforcement, quality assurance, and governance in regulated environments
Experience designing APIs and microservices for analytics and ML platforms
Excellent written and verbal communication, including briefing senior, non-technical audiences
U.S. citizenship or lawful permanent residency may be required per contract
Ability to obtain a federal government Public Trust or security clearance where required
Bachelor's or advanced degree in Computer Science, Data Science, Statistics, Engineering, or a related field, or equivalent professional experience
Experience with large language model applications, retrieval-augmented generation, embeddings, vector databases, evaluation, and guardrails
Microsoft Azure certifications or equivalent AWS or Google Cloud certifications
Experience with Databricks, Snowflake, Microsoft Fabric, or similar enterprise-scale data platforms
Familiarity with FedRAMP, FISMA, and federal data security requirements
Experience supporting a federal agency, or health, scientific, or research data
An active federal Public Trust or security clearance is an additional qualification

Benefits

Comp & perks

Discretionary bonuses
Signing or retention incentives
Other variable compensation may be available
Remote work
Occasional travel
Equal employment opportunity and inclusive workplace commitments