AI/ML Engineer (R-00194)

True Zero Technologies is a veteran-owned small business providing technology and security services to government customers. The AI/ML Engineer designs, builds, integrates, deploys, and operates AI and machine learning capabilities in secure government cloud environments, supporting the full AI/ML lifecycle. The role also develops Python applications, Generative AI and RAG solutions, integrations, evaluations, monitoring, and optimization aligned with security and compliance requirements.

Responsibilities

• 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
• 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
• 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

Preferred

• AWS Certified AI Practitioner
• AWS Certified Machine Learning Specialty

Benefits

• 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

Company

• Cybersecurity consulting and managed security services
• Fairfax, Virginia, USA
• https://truezerotech.com/
• Founded in 2016
• 51-200 employees

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
• AWS Certified AI Practitioner
• AWS Certified Machine Learning Specialty

Required skills

• Containerized Workloads and Microservices, Embeddings, Foundation Models, Generative AI, Large Language Model (LLM) Evaluation, MLOps/LLMOps, Machine Learning, Prompt Engineering, Retrieval-Augmented Generation (RAG), Security-Sensitive Environments, Semantic Retrieval, Vector Search

Preferred skills

• AWS Certified AI Practitioner, AWS Certified Machine Learning Specialty

Experience

• Mid level