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

Intertwine Associates partners with government and other organizations to deliver operational efficiency, tailored frameworks, and technology-driven impact. The Senior AI / Data Engineer will lead the design and delivery of enterprise data platforms, machine learning systems, and AI applications, while setting engineering standards, advising client leadership, and mentoring multidisciplinary teams.

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

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
• 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