The AI/ML Engineer is responsible for designing, building, integrating, deploying, and operating artificial intelligence and machine learning capabilities that support mission and business workflows in secure government cloud environments. This role spans the AI/ML lifecycle, including data preparation, model and application development, evaluation, deployment, monitoring, and ongoing optimization.
The engineer will leverage FedRAMP-authorized services available within AWS GovCloud, while ensuring all AI/ML solutions align with applicable security, data handling, compliance, and Zero Trust requirements. The ideal candidate has strong Python development skills, experience with modern AI/ML architectures and data pipelines, and practical knowledge of deploying and evaluating models in cloud environments.
Job ResponsibilitiesAI/ML Engineering & Mission Integration- Build and integrate AI/ML capabilities supporting mission workflows using FedRAMP-authorized services available in AWS GovCloud, from data preparation through deployment, evaluation, and monitoring.
- Design, develop, test, and operationalize AI/ML solutions aligned to defined mission and business requirements.
- Translate operational use cases into scalable AI/ML architectures, services, and integration patterns.
- Develop APIs, services, and application integrations that expose AI/ML capabilities to mission applications and enterprise platforms.
- Collaborate with application engineers, data engineers, cloud engineers, cybersecurity teams, and mission stakeholders throughout the solution lifecycle.
- Conduct technical evaluations and proof-of-concept implementations to determine whether proposed AI/ML technologies are appropriate for the mission, security environment, and available GovCloud services.
- Maintain technical documentation covering architecture, model behavior, interfaces, dependencies, deployment procedures, and operational requirements.
Python & AI/ML Development- Develop production-quality AI/ML applications and supporting services using Python.
- Build reusable Python modules, services, utilities, and automation supporting data processing, inference, evaluation, and system integration.
- Apply standard software engineering practices including source control, automated testing, code review, dependency management, and CI/CD.
- Develop and integrate machine learning models, foundation models, or AI services based on approved use cases and architecture.
- Optimize AI/ML application performance, reliability, scalability, and resource utilization.
- Troubleshoot issues involving model behavior, data quality, application integration, cloud services, and runtime environments.
Generative AI & Retrieval-Augmented Generation- Design and implement Generative AI and Retrieval-Augmented Generation (RAG) patterns when included within the approved solution scope.
- Develop workflows for document ingestion, parsing, chunking, embedding generation, indexing, retrieval, prompt construction, and model inference.
- Integrate approved large language models and foundation-model services with enterprise applications and mission data sources.
- Evaluate retrieval quality, response relevance, groundedness, hallucination risk, and overall solution effectiveness.
- Develop prompt-management, model-routing, and orchestration patterns where appropriate.
- Implement safeguards and validation mechanisms to reduce the risk of inappropriate, inaccurate, or unauthorized model outputs.
- Support secure integration of vector stores, search services, knowledge repositories, and other components required by RAG architectures.
Job Qualifications- Bachelor's degree in Cybersecurity, Computer Science, Information Technology, Information Systems, or a related technical discipline.
- Experience with Generative AI, foundation models, and RAG architectures, where applicable to the program scope.
- Experience with embeddings, vector search, semantic retrieval, prompt engineering, and LLM evaluation.
- Experience with supervised or unsupervised machine learning, feature engineering, model training, and model selection where traditional ML is in scope.
- Familiarity with MLOps or LLMOps practices for model and application lifecycle management.
- Experience developing automated model and application evaluation frameworks.
- Familiarity with responsible AI concepts, including model limitations, bias evaluation, explainability, traceability, and human oversight.
- Experience deploying containerized workloads and microservices.
- Experience working in government, defense, regulated, or other security-sensitive environments.
Preferred Certifications:- AWS Certified AI Practitioner
- AWS Certified Machine Learning Specialty
We're actively searching for talented security and technology practitioners who are ready to experience the True Zero difference. As a True Zero team member, you'll enjoy:
- Competitive salary, paid twice per month
- Best in class medical coverage
- 100% of medical premiums covered by True Zero
- Company wide new business incentive programs
- Contribution Incentives (i.e. white papers, blog posts, internal webinars, etc.)
- 3 weeks of PTO starting + 11 Paid Holidays Annually
- 401k Program with 100% company match on the first 4%
- Monthly reimbursement of Cell Phone and Home Internet costs
- Paternity/Maternity Leave
- Investment in training and certifications to broaden and deepen your technical skills
