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

Intertwine Associates•Mount Pleasant, SC

2d•$130,000 - $175,000•Remote

About The Position

Work in a dynamic, fast-paced environment as a Senior AI / Data Engineer supporting federal agencies and other clients. Lead the design and delivery of the data platforms, machine learning systems, and AI applications that turn client data into decisions, and set the engineering standards other engineers follow. Strong client or customer engagement is required in this role. You will work directly with client program leadership, architects, data scientists, and governance teams, advise on technical direction, and represent Intertwine Associates and the client with professionalism, responsiveness, and sound judgment at every touchpoint. This is a remote position with occasional travel. Assignments are matched to client needs and to each candidate's expertise and eligibility.

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, with experience integrating relational and unstructured sources.
Deep hands-on experience with Azure data services, or equivalent depth in 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 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 the assignment requires one.

Nice To Haves

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: 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, 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.

Responsibilities

Architect and lead the delivery of enterprise data platforms and pipelines on Azure (Data Lake Storage, Azure SQL, Data Factory, Microsoft Fabric / Foundry) or equivalent cloud services.
Set standards for ETL design, schema enforcement, data validation, quality checks, and lineage, and review other engineers' work against them.
Design, build, and deploy machine learning and AI solutions, including applications built on large language models such as retrieval-augmented generation, document understanding, and agentic workflows, with evaluation and guardrails.
Build secure API endpoints and microservices that make data and models available to analytics and ML platforms.
Establish MLOps practices: 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.