ROLE OVERVIEW
Red Arch Solutions is seeking an experienced AI/ML Data Engineer to collaborate on the design and implementation of enterprise-scale data platforms supporting a large-scale Agentic AI transformation initiative.
With extensive experience delivering AI and machine learning solutions in complex enterprise environments, you will be responsible for architecting the data ecosystem that powers vector search, Retrieval-Augmented Generation (RAG), large language model (LLM) applications, and emerging Agentic AI capabilities. You will work across infrastructure, cybersecurity, software engineering, and mission stakeholders to rapidly deliver scalable, secure, and reliable AI solutions.
This role requires a seasoned engineer capable of communicating complex technical concepts and architectural tradeoffs to senior leaders, helping leadership teams understand the operational, mission, security, and business implications of emerging AI technologies while driving successful implementation of enterprise capabilities.
The Red Arch Distinction: People First
Red Arch Solutions is a flat, highly collaborative organization where your voice is heard. We prioritize work/life balance and individualized professional growth, backed by a 100% company-paid healthcare model, a robust annual training allocation, and an elite technical community solving our nation's most urgent national security challenges.
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.
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.
Technology Evaluation: Assess emerging AI technologies, vector database platforms, retrieval frameworks, and engineering approaches to improve organizational AI capabilities.
REQUIRED QUALIFICATIONS Clearance: Active, current Top Secret / SCI with Polygraph is mandatory.
Education: Bachelor’s degree in computer science, Engineering, Mathematics, Data Science, or a related quantitative discipline. Equivalent experience may be considered.
Experience:
10+ 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.
Extensive experience designing data pipelines supporting machine learning models, vector databases, semantic…