Artificial Intelligence and Machine Learning Engineer, Mid

Booz Allen Hamilton is seeking an experienced AI and ML engineer to develop and operationalize secure, scalable AI solutions. The role involves collaborating with cross-functional teams to deliver impactful AI and ML solutions and modernizing an AI-driven platform.

Responsibilities:

• Help develop and operationalize secure, scalable, production-grade AI solutions that sustain and advance mission-critical capabilities
• Work as part of a cross-functional team, collaborating with data engineers, data scientists, solution architects, and product owners to deliver high-impact AI and ML solutions across a broad range of use cases
• Modernize and operate an end-to-end, AI-driven platform built on Databricks, Palantir, Amazon Bedrock, and custom AI and ML models
• Sustain and enhance batch and streaming data pipelines
• Improve data quality, lineage, and observability
• Partner with data engineers and subject matter experts (SMEs) to define data contracts and feature pipelines
• Modernize legacy case selection capabilities by decomposing them into scalable services and operationalizing rules and model-driven scoring, prioritization, routing, and human-in-the-loop review
• Build and operate production-grade ML pipelines with strong MLOps practices, including versioning, CI/CD, monitoring, drift detection, explainability, and fairness
• Integrate with shared enterprise services using API-first and event-driven patterns
• Harden the platform to meet security and compliance requirements, including ATO
• Produce architecture and operational documentation
• Collaborate closely with product, fraud, and case management teams in an Agile delivery environment

Requirements:

• Experience building, deploying, and operating production ML models such as supervised, unsupervised, and anomaly detection, including techniques for imbalanced datasets
• Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining
• Experience with Python and ML frameworks such as scikit-learn, PyTorch, or TensorFlow
• Experience with Palantir and data engineering platforms such as Databricks, Spark, or SQL, and batch and streaming pipelines
• Experience improving data quality, lineage, and observability in enterprise data environments and operationalizing rules and model-driven scoring for prioritization, routing, or case selection
• Experience with API-first and event-driven integration patterns, including secure service-to-service communication
• Knowledge of responsible AI practices, including explainability, fairness, and bias assessment
• Ability to design and document architecture artifacts, data contracts, and operational runbooks
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
• Bachelor's degree and 2+ years of experience with DevOps, software, or data engineering, or 5+ years of experience with DevOps, software, or data engineering in lieu of a degree
• Experience working in Agile delivery environments, collaborating with product owners, SMEs, and engineering teams
• Experience with fraud detection, risk analytics, or case selection in government, tax, or financial domains
• Experience with Amazon Bedrock and integrating custom AI models into enterprise workflows
• Experience deploying ML solutions in AWS GovCloud or other regulated cloud environments
• Experience with federal ATO processes, continuous compliance, and operating systems under FISMA controls
• Experience in enterprise modernization programs such as cloud migration, microservices, API strategy, and DevSecOps
• Knowledge of graph-based analytics and advanced anomaly detection techniques
• AWS Machine Learning Specialty, Security+, AI Engineer, or similar Certification