Job description

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: • 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 #CJ The Red Arch Solutions pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Determination of official compensation or salary relies on several factors including, but not limited to, level of position, job responsibilities, geographic location, scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements, alignment with local internal equity as well as alignment with market data. Red Arch Solutions Benefits Snapshot: • 100% paid employee healthcare premiums. CareFirst Advantage Best in Class Benefits. • HaloScripts Concierge prescription medication service • Generous PTO. • 10 % 401K 6% match vested day one and up to 4% profit sharing contribution. • Annualized bonus compensation. • Spot bonuses for hard work. • Tuition reimbursement. • 529 College Saving Plan. • College Loan Pay Back Program. • 11 Paid Federal Holidays • Generous Referral Bonuses. Red Arch Solutions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Have more questions about Red Arch? Email us at Careers@RedArchSolutions.com

Requirements

Must-haves

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.
The Red Arch Distinction: People First
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.
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.

Nice-to-haves

Annualized bonus compensation.

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Keywords to mirror

aimlmachine learningllmpythonsqlazureawsci/cd

Platform: jazzhr
Effort: medium

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