Integral partners with federal defense, intelligence, and civilian leaders to tackle mission-critical challenges and deliver measurable outcomes. In this hybrid role in Tysons Corner, VA, you’ll join the internal core technical group within Integral’s Office of Technology to build and operationalize data architectures that power AI and machine learning capabilities for secure federal environments. The work blends scalable data engineering with AI/ML integration, including LLM-focused evaluation and deployment, while collaborating closely with government stakeholders.
What you’ll do
- Design, build, and optimize scalable data architectures that support advanced ML models, analytics, and high-volume processing for federal mission sets.
- Develop, construct, test, and maintain resilient ETL/ELT pipelines, including pipelines supporting synthetic data.
- Process and integrate high-velocity structured and unstructured multimodal data including text, imagery, sensor data, and audio/video.
- Evaluate and deploy AI models, including Large Language Models, while ensuring they are tuned for performance, accuracy, and scalability in secure environments.
- Interface with Integral project personnel and federal government stakeholders to gather requirements, translate mission needs into data solutions, and present technical concepts to non-technical leaders.
- Lead internal, non-billable capability development, with the agility to deploy onto billable client engagements as required.
- Ensure data pipelines and ML architectures adhere to federal security, privacy, and data governance standards (including NIST, FISMA, and DoD Cloud Computing SRG).
Key requirements
- Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, or a related highly technical field.
- 3+ years of progressive data engineering experience, including 2+ years focused on Artificial Intelligence and Machine Learning operations (MLOps).
- Strong experience working in cloud environments, especially AWS GovCloud or Azure Government.
- Expert-level proficiency in Python and SQL, plus data manipulation libraries such as Pandas and PySpark.
- Proven experience building complex ETL/ELT pipelines for unstructured and multimodal data.
- Hands-on experience evaluating, fine-tuning, and deploying AI models using tools such as HuggingFace, PyTorch, and TensorFlow.
- Experience with data warehousing and data lake architectures including Databricks, Snowflake, and Redshift.
- Must be eligible to obtain and maintain at least a DoD Secret Clearance.
Tools you’ll work with
Python, SQL, Pandas, PySpark, HuggingFace, PyTorch, TensorFlow, Databricks, Snowflake, Redshift, AWS GovCloud, Azure Government
Preferred qualifications
- Active DoD Secret, Top Secret, or TS/SCI clearance (desirable).
- Master’s degree in Data Science, AI, or a related field.
- Prior consulting or direct experience with the DoW, Intelligence Community, or DHS.
- Deep understanding of MLOps frameworks, containerization (Docker, Kubernetes), and CI/CD pipelines for machine learning.
Compensation and benefits
Salary range: $150,000 - $200,000 per year.
- Paid parental leave
- Immediate vesting in 401(k)
- Medical, Dental & Vision Insurance
- Flexible Spending Accounts
- Short-Term and Long-Term Disability Insurance
- Life Insurance
- Paid Time Off & Holidays
- Earned Bonuses & Awards
- Professional Training Reimbursement
- Employee Assistance Program
Clearance requirement: Ability to obtain and maintain a DoD Secret Clearance (Active Secret or higher preferred).
