Data Architect & Solutions Engineer for Federal Platforms

Jamal Natour

Target Roles: Applied AI/ML Architect; Solutions Architect; Cloud and Data Architect

Washington, DC Area • 703-***-**** • ***********@*****.*** • https://www.linkedin.com/in/jamal-natour-33412b150/

PROFESSIONAL SUMMARY

Applied AI/ML Architect bridging modern GenAI capabilities with 18+ years of federal sector experience delivering mission-critical systems for DoD, State, Commerce, Energy, and DHS. Security clearance eligible (held DoD Top Secret/Secret 2003-2021). Expertise in architecting and deploying secure, production-grade GenAI solutions for regulated enterprises, with deep experience in multi-provider LLM orchestration (OpenAI API, Azure OpenAI), RAG implementations, and secure hybrid architectures. Deep understanding of federal technology evolution from workflow automation (2000s) through cloud modernization (2010s) to current AI transformation, with proven ability to navigate federal procurement, collaborate with systems integrators, and deliver compliant solutions. Product-minded architect who transforms government operations by identifying high-value GenAI applications and driving them from prototype to production.

Federal Impact: Led 40+ person teams; architected USXPORTS serving all USG export licensing; delivered $20M+ in contract wins; modernized agency operations through search platforms and cloud transformation.

SKILLS, PLATFORMS, AND TECHNOLOGIES

Cloud: Multi-cloud Architecture (AWS, Azure, GCP)

Data and Analytics: Databricks Spark, Delta Lake, Unity Catalog; Snowflake RBAC and Secure Sharing; ADLS Gen2

AI and ML: OpenAI API; Azure OpenAI; RAG; vector databases; MLflow; Python; FastAPI; model evaluation; prompt and version management; microservices; containerization

Security and Networking: Azure AD SSO; OAuth and SAML; RBAC; Key Vault; Private Endpoints; Application Gateway; WAF; NSGs; SGs; VNets; VPCs; DLP; PHI and PII protections; HIPAA and HITRUST

DevOps and IaC: Azure DevOps CI/CD; ARM and Bicep; Docker; Kubernetes; DataOps patterns

Search and Text: Elasticsearch, Solr; NLP tokenization, lemmatization, query expansion

Languages: Python, JavaScript/TypeScript, SQL, Java, C#, PowerShell, Linux, UNIX

Principles & governance: reference architectures, implementation roadmaps, design reviews, standards, model governance (MLflow), SLOs/error budgets, cost guardrails.

PROBLEMS I SOLVE, PATTERNS I USE, IMPACT I DELIVER

- Ship production GenAI safely in regulated settings. Patterns: RAG with hybrid retrieval; vector stores; prompt and version management; LLM orchestration; secure endpoints; evaluation and drift monitoring; responsible AI guardrails. Impact: revenue-generating AI features; faster analysis (translation/OCR/summarization); auditable.

- Modernize data platforms for scale, governance, and AI readiness. Patterns: Lakehouse (Bronze/Silver/Gold); Delta (Liquid Clustering); Snowflake RBAC and Secure Sharing; ADLS Gen2; Unity Catalog. Impact: hours to minutes; governed self-service; pay-per-use cost control.

- Engineer reusable platform foundations. Patterns: IaC modules; golden paths; service catalog; metering/chargeback; SLOs; runbooks. Impact: time-to-first-service weeks to days; predictable delivery; measurable cost/performance gains.

PROFESSIONAL EXPERIENCE

Independent Consultant - Remote

Independent Consultant (Applied AI/ML Architect) March 2025 to Present

- Delivered LLM experimentation on a cloud-agnostic path in the client’s primary cloud (Azure, AWS, or GCP): managed APIs (Azure OpenAI), managed serving (Databricks/Azure ML/SageMaker/Vertex), or self-host (Llama via vLLM/Ollama), guided by a speed/control/cost rubric.

- Built production-minded RAG systems: prompt templates, tool/function calling with JSON schemas, retrieval access filters, and citation rules; set latency and output-length budgets.

- Beyond RAG, piloted parameter-efficient fine-tuning (LoRA/QLoRA) with MLflow tracking; canary deploys with rollback.

- Stood up evaluation & observability: golden sets, automatic faithfulness/groundedness/exact-match metrics, p95/p99 latency, cost/token, and drift alerts; trace IDs for query to retrieval to generation.

- Implemented guardrails: PII/toxicity filters, rate limits, kill-switches, access reviews; per-tenant quotas / budget caps.

- Right-sized serving: autoscale endpoints/queues, quantization where appropriate, and structured error handling for resilience.

Berkeley Research Group (BRG) - Remote

Director of IT, Expert Solutions, and Principal Solutions Architect Jun 2022 to Feb 2025

- Owned AI and data architecture for Expert Solutions; launched 7 internal services; ~85% adoption across 500+ experts; ~$5M new ARR.

- Built production GenAI: LLM orchestration layer, RAG over proprietary data, prompt/version management, and evaluation harness; reduced tickets and cycle time.

- Enabled multi-provider LLM strategy: Azure OpenAI plus fine-tuned OSS models with policy controls and fallbacks; avoided lock-in and improved resilience.

- Established MLOps at scale: MLflow tracking/registry; automated CI/CD; drift/quality monitoring.

- Fine-tuned Llama on proprietary data, delivering ~25% accuracy lift versus baseline APIs on specialist tasks.

- Drove security/compliance: OAuth/SAML SSO; Zero Trust patterns; PHI/PII controls in HIPAA/HITRUST.

- Set data governance: data contracts, quality SLAs, lineage; fewer breakages; faster onboarding.

- Modernized analytics on Azure/AWS with Databricks and Snowflake (Delta with Liquid Clustering; OPTIMIZE/VACUUM; Unity Catalog; SSO; Private Endpoints); result: worst-case 30 hours to under 30 minutes; migrated 10–15 teams; ~40% infrastructure savings.

- Shipped OCR (~5M pages/year) and Translation (~12K docs/month) with automated chargeback; maintained 99.9% SLOs; productized Query Optimization.

- Built service catalog + golden paths (scaffolds, CI/CD, IaC); time-to-first-service weeks to days.

Berkeley Research Group (BRG) - Remote

Senior Cloud Architect Jun 2021 to May 2022

- Established AWS/Azure landing zones and data foundations (ADLS Gen2, Databricks, Snowflake with RBAC/SSO); integrated Power BI/Tableau; implemented Private Endpoints and Zero Trust patterns.

- Migrated SQL Server workloads to Snowflake; centralized RBAC/SSO, cost tagging; reduced infrastructure cost 40%.

- Ran Databricks vs. Snowflake evaluations and set governance standards (Delta/Unity, secure sharing, data contracts).

SalientCRGT - Alexandria, VA

Technical Director and Senior Cloud Architect Mar 2019 to Jun 2021

- Led cloud modernization for federal agencies (DoD, DoS, DoC, DoE, DHS), managing $10M+ portfolio while collaborating with systems integrators (Booz Allen, GDIT, CACI) to deliver NIST 800-171/CMMC-compliant architectures for mission-critical government operations.

- Architected secure hybrid cloud solutions integrating on-premise systems with Azure Government Cloud, implementing Private Endpoints, Azure Key Vault, and Zero Trust patterns to enable secure data processing and analytics while maintaining air-gapped security for classified information.

- Navigated complex federal acquisition processes, security clearance requirements, and multi-agency governance frameworks; served as technical authority during contract re-competitions, contributing to $20M+ in wins through demonstrated cloud innovation, compliance expertise, and proven ability to coordinate multi-vendor teams including prime contractors and systems integrators..

- Prototyped predictive analytics and classification models using Python scikit-learn and TensorFlow for anomaly detection in federal datasets, establishing early patterns for machine learning adoption in government systems.

Salient Federal Solutions - Arlington, VA

Technical Director and Solutions Architect Jun 2011 to Mar 2019

- Architected enterprise search platforms for federal defense and intelligence agencies, implementing Elasticsearch/Solr with custom NLP pipelines (tokenization, lemmatization, entity extraction) to enable secure information retrieval across classified (SIPR) and unclassified (NIPR) networks.

- Led technical vision for multi-agency systems supporting DoD, State, and Commerce, introducing predictive analytics models and Apache Zeppelin for collaborative data analysis while maintaining CMMI Level 3 compliance.

- Drove agile transformation across federal programs, implementing early DevOps practices that reduced deployment cycles from months to weeks while maintaining security accreditation.

- Served as key technical resource in winning multiple contract re-competitions, demonstrating innovation through advanced search technologies and data analytics capabilities.

ATSC - Arlington, VA

Principal Task Leader and Technical Director Jan 2003 to May 2011

- Architected and delivered USXPORTS, the US Government's mission-critical export control system processing all export license applications across State, Commerce, Defense, and Energy departments; system featured sophisticated workflow engine, business rules-based decision support, and integration with third-party compliance APIs (LexisNexis).

- Led 40+ developers during initial system deployment under prime contractor SRA, then managed seamless transition to follow-on enhancement phase, demonstrating systems integrator collaboration expertise.

- Achieved ~40% analyst productivity improvement by engineering a decision-support workflow that integrated third-party compliance data APIs with a custom-built Solr/Lucene platform for precedent case analysis.

- Instrumental in achieving CMMI Level 3 certification and winning consecutive contract re-competitions through continuous innovation in workflow automation and user-specific customization capabilities.

EDUCATION

MS, Electrical Engineering - University of Florida (Gainesville, FL)

BS, Electrical Engineering - University of Florida (Gainesville, FL)

CERTIFICATIONS

Azure Solutions Architect Expert; Microsoft Data Scientist Associate; Microsoft AI Fundamentals; Security+; SAFe Agilist; Scrum Master; ITIL

SECURITY CLEARANCE

Eligible for reinstatement - Previously held active DoD Top Secret / DoD Secret clearances (2003 - 2021)

DOMAINS AND CONTEXTS

Federal Agencies: DoD (OUSD(P), DISA), State (export control), Commerce (BIS), Energy, DHS

Clearance History: DoD Top Secret/Secret (2003-2021)

Systems Integrators: SRA, Booz Allen, GDIT, CACI collaboration

Compliance: NIST 800-171, CMMC, FedRAMP, CMMI Level 3, export control regulations

Federal Systems: USXPORTS, SPAN, SIPR/NIPR networks

Technologies: Cloud migration, search platforms, NLP, workflow automation

Commercial: Supporting Fortune 500 government contractors through BRG platform (2021-2025).

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