Senior AI/ML Data Engineer KEY RESPONSIBILITIES- Enterprise AI Platform Engineering: 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.
- Data Architecture & Strategy: Establish and implement controls for data quality, lineage, source attribution, prompt and context traceability, explainability, and evaluation of AI system outputs.
- AI Data Governance: Establish and implement controls for data quality, lineage, source attribution, prompt and context traceability, explainability, and evaluation of AI system outputs.
- Technical Leadership: Lead architectural decision-making for AI-supporting data infrastructure, balancing performance, scalability, security, reliability, maintainability, and cost considerations.
- Cross-Functional Integration: Partner with Data Scientists, Machine Learning Engineers, Architects, Cybersecurity teams, and Software Engineers to translate AI requirements into production-grade capabilities.
- Executive Communication: Translate highly technical AI, machine learning, and data architecture concepts into clear operational impacts, risks, opportunities, and implementation considerations for senior leadership.
- Enterprise Coordination: Coordinate with stakeholders across multiple organizations to align AI initiatives, maximize reuse of enterprise capabilities, and eliminate duplication of effort.
- Operational Excellence: Implement monitoring, observability, and alerting to ensure the reliability, performance, and continuous improvement of AI-supporting data platforms.
- Mentorship & Engineering Excellence: Provide technical leadership and mentorship to engineers while promoting engineering best practices and innovation across the organization.
- Technology Evaluation: Assess emerging AI technologies, vector database platforms, retrieval frameworks, and engineering approaches to improve organizational AI capabilities.
Experience and Qualifications:To be eligible for this demanding position, the ideal candidate should demonstrate the following experience and qualifications:
Required Education and Years of Experience:- 20 Years of experience in AI/ML, Data, or Software Engineering roles or a highly related field of work with similar scope and responsibilities.
- A Bachelor's degree may be substituted for 4 years of experience and a Master's Degree may be substituted for 6 years of experience.
Required Qualifications: - Active TS/SCI with CI Polygraph
- Expert proficiency in Python, SQL, and modern software engineering practices.
- Deep experience with Azure, AWS, or Google Cloud data and AI platforms.
- Strong understanding of distributed systems, cloud-native architectures, MLOps, and AI platform engineering.
- 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.
Desired Qualifications: - 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.
- Extensive experience designing data pipelines supporting machine learning models, vector databases, semantic search capabilities, and generative AI applications.
- Proven experience delivering complex technical solutions from strategic requirements through operational deployment while balancing schedule, performance, capability, and cost objectives.
- Experience building and operating enterprise-scale vector search, RAG, knowledge management, and LLM-based platforms.
- Experience supporting AI adoption efforts within large government, defense, intelligence, or highly regulated organizations.
Telework/Remote Availability: Hybrid work authorized (minimum 2-3 days onsite)
Work Location(s): Washington, DC or Reston, VA
Contingent Upon Program AwardThe position is contingent upon program award.
Summary Pay Range:Please note that the information shown below is a general guideline only. Pay is based upon candidate experience and qualifications, as well as market and business considerations.
$242,000 - $305,000
