AL/ML Data Scientist - AI, Vector Search & Agentic AI Platforms

United States·Restonmid

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Quick Summary

Key Responsibilities

Architect, build, and maintain enterprise-scale data platforms supporting vector databases, semantic search, Retrieval-Augmented Generation (RAG), Agentic AI systems,

Requirements Summary

Translate highly technical AI, machine learning, and data architecture concepts into clear operational impacts, risks, opportunities, and implementation considerations for senior leadership.

Technical Tools

Data ScientistData

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:
12+ 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 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.

Technical Expertise

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.

Communication & Leadership

Exceptional written and verbal communication skills.
Ability to communicate complex technical concepts to both technical and non-technical audiences.
Proven ability to explain AI, machine learning, and data architecture concepts in terms of mission impact, operational outcomes, technical risk, and implementation tradeoffs.
Experience influencing decisions and driving consensus among diverse technical and business stakeholders.

DESIRED SKILLS & FRAMEWORKS

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 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.

Salary Range for this role $220-250K
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