AI Engineer
Indexed description
As an AI Engineer, you will leverage statistical and AI/ML algorithms to deliver advanced analytics, including predictive analysis and modeling, pattern-of-life analysis, and remote sensing change detection. You will manage the entire AI/ML development lifecycle from design and training to deployment and maintenance while ensuring performance, observability, and security. This role contributes to building scalable infrastructure, real‑time dashboards, and automated pipelines that enable secure, compliant, and efficient AI operations aligned with mission and business goals.
Key Responsibilities Include
- Lead end-to-end data science initiatives, encompassing the design, training, and production deployment of AI/ML algorithms in IL5/IL6 environments.
- Utilizing data pipelines in Databricks, Apache Spark, and related ETL technologies (e.g., AWS Glue, Apache Airflow).
- Ensuring compliance with DoD security and accreditation standards, including STIGs and Impact Level controls.
- Providing architectural oversight on data ingestion, curation, and storage to produce reliable, high-quality datasets for AI/ML development.
- Supporting DevSecOps practices, CI/CD pipelines, and automation to streamline delivery.
- Must be a US Citizen with the ability to obtain a TS/SCI + CI Poly security clearance
- Bachelor’s degree in Computer Science, Electrical Engineering, or a related technical field
- 5+ years of experience in software engineering, data engineering, and cloud architecture
- Proven ability to conduct advanced data analysis and apply data science methodologies for predictive modeling, pattern of life analysis, and change detection analysis
- Proficiency in Python, C++, and JavaScript
- Proficiency in Linux -- system administration, scripting in Bash, troubleshooting
- Strong expertise in AWS cloud services (compute, storage, networking, IAM)
- Strong foundation in AI/ML algorithms and ability to implement agentic workflow, and prompt engineering
- Experience in large language model (LLM) applications
- Strong understanding of model evaluation metrics (e.g., precision, recall, AUC) and statistical drift detection methods
- Expertise in containerization and orchestration (Docker, Kubernetes, OpenShift) and CI/CD automation (GitHub Actions, Jenkins)
- Experience with time-series databases and relational databases
- Proficiency in building and managing ETL pipelines (e.g. AWS Glue, Apache Airflow)
- Strong communication skills with the ability to interface and collaborate with project managers, stakeholders, vendors, and technical staff
- Active TS/SCI security clearance with CI Poly
- Master’s degree in Computer Science, Electrical Engineering, or a related technical field
- Prior experience supporting DoD, Intelligence Community, or other U.S. Government programs
- Understanding security accreditation processes for IL5/IL6 environments
- Experience with the following:
- Computer graphics and computer vision AI/ML
- Remote sensing (SAR, EO/IR, MSI, etc.)
- GIS
- Principle component analysis (PCA)/linear discriminant analysis (LDA)
- K-nearest neighbors (KNN)/Clustering techniques
- Bayesian science/Bayes naive network
- Reinforcement Learning (RLHF, PPO, DQN, etc.)
- Variational auto encoders (VAEs)
- Retrieval‑Augmented Generation (RAG) with Graph DB and Relational DB
- Optimization algorithms
- Kalman filtering
- Network and RF communications
- Signal processing
- High performance computing (HPC)
- PostgreSQL, Elastic, MongoDB, Graph DB for supporting data engineering workflows
- Data governance, metadata management, and compliance frameworks
Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow.
We Value
- Attracting and developing top talent and high-performing teams
- Fostering a culture that is engaging, accountable, and mission-driven
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