Note: The job is a remote job and is open to candidates in USA. 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
Skills
- 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
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 Overview