Senior AI/ML Data Engineer

The Senior AI/ML Data Engineer will serve as a technical leader responsible for architecting the data ecosystem that powers vector search, Retrieval-Augmented Generation (RAG), large language model (LLM) applications, and emerging Agentic AI capabilities in support of Apavo’s DoD and Intelligence Community clients. This role works across infrastructure, cybersecurity, software engineering, and mission stakeholders to rapidly deliver scalable, secure, and reliable AI solutions, and is expected to communicate complex technical concepts and architectural tradeoffs to senior leaders and mission stakeholders.

Duties & Responsibilities:

Senior AI/ML Data Engineer responsibilities include, but are not limited to:

• Architect, build, and maintain enterprise-scale data platforms supporting vector databases, semantic search, Retrieval-Augmented Generation (RAG), Agentic AI systems, and large language model applications
• Establish and implement controls for data quality, lineage, source attribution, prompt and context traceability, explainability, and evaluation of AI system outputs
• Lead architectural decision-making for AI-supporting data infrastructure, balancing performance, scalability, security, reliability, maintainability, and cost
• Partner with Data Scientists, Machine Learning Engineers, Architects, Cybersecurity teams, and Software Engineers to translate AI requirements into production-grade capabilities
• Translate highly technical AI, machine learning, and data architecture concepts into clear operational impacts, risks, opportunities, and implementation considerations for senior leadership
• Coordinate with stakeholders across multiple organizations to align AI initiatives, maximize reuse of enterprise capabilities, and eliminate duplication of effort
• Implement monitoring, observability, and alerting to ensure the reliability, performance, and continuous improvement of AI-supporting data platforms
• Provide technical leadership and mentorship to engineers while promoting engineering best practices and innovation across the organization
• Assess emerging AI technologies, vector database platforms, retrieval frameworks, and engineering approaches to improve organizational AI capabilities

The Senior AI/ML Data Engineer is expected to have additional duties as assigned in support of corporate cyber security services. Additional details are reviewed in accordance with company policies.

Requirements

Qualifications

• Active, current Top Secret/SCI with Polygraph clearance is mandatory

• Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related quantitative discipline (equivalent experience considered)

• 20+ years of progressive experience in software engineering, data engineering, distributed systems, cloud architecture, or AI/ML platform development

• Proven experience designing and delivering enterprise-scale AI, machine learning, generative AI, or Agentic AI solutions

• Demonstrated success architecting and implementing production cloud-native data systems supporting advanced analytics and AI workloads

• Proven experience working within complex enterprise environments managing security, infrastructure, technology dependencies, governance requirements, and competing priorities

• Expert proficiency in Python, SQL, and modern software engineering practices

• Deep experience with Azure, AWS, or Google Cloud data and AI platforms

• Experience implementing vector databases, embedding pipelines, retrieval systems, and Retrieval-Augmented Generation architectures

• Experience with CI/CD pipelines, orchestration platforms, infrastructure automation, and observability tooling

• Exceptional written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences

• Proven ability to influence decisions and drive consensus among diverse technical and business stakeholders

Desired Skills & Frameworks:

• Experience serving as a Principal Engineer, Lead Data Engineer, Solution Architect, or Technical Lead

• Experience building and operating enterprise-scale vector search, RAG, knowledge management, and LLM-based platforms

• Hands-on experience with large-scale distributed data processing frameworks

• Experience leading engineering teams and mentoring junior and mid-level engineers

• Experience supporting AI adoption efforts within large government, defense, intelligence, or highly regulated organizations

• Familiarity with AI governance, model evaluation frameworks, explainability, and responsible AI implementation practices