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

Intertwine Associates LLC; Mount Pleasant (SC); Remote; USD 130,000 - 175,000; Full time

Job summary

Intertwine Associates LLC is seeking a senior data engineering and AI leader to design and deliver Azure-based data platforms, ML/AI applications, and secure APIs. You will set engineering standards, collaborate with client teams, and mentor engineers across multidisciplinary groups.

The role is remote with a base in Mount Pleasant, SC, offering a base salary in the $130,000–$175,000 range, plus discretionary bonuses and incentives that are not guaranteed.

Qualifications

• 7+ years building data pipelines, ML systems, or AI apps in production.
• 2+ years of leading technical work.
• Expert Python with Pandas and NumPy; advanced SQL.
• Deep Azure data services experience; cloud knowledge across AWS or GCP is a plus.
• Production ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience with governance, data validation, and compliance in regulated environments.
• Ability to brief senior non-technical audiences.

Responsibilities

• Architect and lead enterprise data platforms and pipelines on Azure.
• Define ETL standards, schema enforcement, data validation, and lineage.
• Design, build, and deploy ML/AI solutions with LLMs and guardrails.
• Build secure APIs and microservices for analytics and ML platforms.
• Implement MLOps: experiment tracking, registries, CI/CD, containers, monitoring.
• Apply governance and federal frameworks (e.g., NIST) for reproducibility and auditability.
• Translate mission needs into technical roadmaps and client briefings.
• Mentor engineers and data scientists across multidisciplinary teams.

Skills

Python

Pandas

NumPy

Advanced SQL

Azure data services

Data governance

APIs & microservices

Communication

Education

Bachelor's or higher in Computer Science, Data Science, Statistics, Engineering

Tools

Azure Data Factory

Azure SQL

Databricks

Snowflake

Microsoft Fabric

Foundry

Job description

Intertwine Associates partners with federal agencies and other clients to deliver modern data and AI systems. In this remote role based in Mount Pleasant, SC, you will lead the design and delivery of Azure-based data platforms, machine learning, and applied AI applications, while setting engineering standards and working closely with client teams.

This position offers an anticipated base salary range of $130,000–$175,000 per year. You may also be eligible for discretionary bonuses, signing or retention incentives, or other variable compensation, which are not guaranteed.

Responsibilities

• Architect and lead enterprise data platforms and pipelines on Azure, including Data Lake Storage, Azure SQL, Data Factory, and Microsoft Fabric / Foundry (or equivalent cloud services).
• Define standards for ETL design, schema enforcement, data validation, quality checks, and lineage, and review other engineers’ work against those expectations.
• Design, build, and deploy machine learning and AI solutions, including applications using large language models such as retrieval-augmented generation, document understanding, and agentic workflows, with evaluation and guardrails.
• Build secure API endpoints and microservices to make data and models available to analytics and ML platforms.
• Implement MLOps practices covering 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, including federal frameworks such as the NIST AI Risk Management Framework.
• Translate mission and business needs into technical roadmaps, estimates, and briefings for client leadership.
• Mentor engineers and data scientists and lead technical work across multidisciplinary teams.

Requirements

• 7+ years of experience building data pipelines, machine learning systems, or AI applications in production, including 2+ years leading technical work.
• Expert Python (including Pandas and NumPy) and advanced SQL, including experience integrating relational and unstructured sources.
• Deep hands-on experience with Azure data services, or equivalent depth with AWS or Google Cloud.
• Production experience with machine learning frameworks such as 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 the ability to brief 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 by the assignment.

Additional Qualifications

• Bachelor’s or advanced degree in Computer Science, Data Science, Statistics, Engineering, or a related field, or equivalent professional experience.
• Experience building applications on large language models, including retrieval-augmented generation, embeddings and vector databases, evaluation, and guardrails.
• Microsoft certifications such as Azure Data Engineer, Azure AI Engineer, Fabric Data Engineer, or Azure Solutions Architect, or equivalent AWS or Google Cloud certifications.
• Experience with Databricks, Snowflake, Microsoft Fabric, or similar modern data platforms at enterprise scale.
• Familiarity with FedRAMP and 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.

Travel Requirements

Remote position with occasional travel.

Technologies: Azure, Data Lake Storage, Azure SQL, Azure Data Factory, Microsoft Fabric, Foundry, Python, Pandas, NumPy, SQL, AWS, Google Cloud, PyTorch, TensorFlow, scikit-learn, retrieval-augmented generation, document understanding, agentic workflows, large language models, APIs, microservices, MLOps, CI/CD, containers, NIST AI Risk Management Framework, Databricks, Snowflake, FedRAMP, FISMA