If asked "why isn't more of this on AWS already?" — this is the honest answer, in order.
Building the same class of system — governance platforms, RAG pipelines, agentic app rationalization — on all three clouds was a deliberate test of what my certifications (AWS DevOps Professional, SA Associate, Cloud Practitioner, GCP ACE, Azure Fundamentals) actually translated into as working production judgment, not just exam knowledge.
Rackspace's Public Cloud Advisory practice has been heavily weighted toward Azure engagements — that's client-driven deal flow, not a personal architecture preference. The EARE platform, the governance platform, Park Agent Chat, and the Content Pipeline all leaned Azure because that's where the client environments already were.
AWS is the only cloud where I pushed to the Professional tier. And even on Azure-hosted systems, the model layer often still defaults to Bedrock — Park Agent Chat and the Content Pipeline both call Claude via Bedrock from Azure compute, and the from-scratch AWS builds (rarf-v4, EARE AWS, Advisory AI Governance) are Bedrock-native end to end. Not universal — Knowledge RAG and Digital Twin's Azure side use Azure OpenAI — but the pattern repeats enough to be a real signal.
I'm not walking in needing to learn Bedrock — I already have rarf-v4 (migration assessment accelerator), EARE AWS (regulated-industry app platform pattern), and the Advisory AI Governance Platform (compliance-as-code accelerator) as production-grade, Bedrock-native, reusable starting points. → Full AWS Solution Mapping
| JD Requirement | Your Evidence |
|---|---|
| 7+ yrs architecting/building/operating on AWS | Strong AWS-centric advisory since 2022 at Onica/Rackspace (Bedrock, Lambda, Step Functions, CloudFormation, DynamoDB), plus AWS S3 migration work at SmarTek21 (2017+) and cloud/hybrid architecture roles going back to RSM (2015) and D+H (2013). 10+ years touching AWS and adjacent cloud infrastructure if you count the full arc. |
| 10+ yrs infrastructure/app/db/network architecture | Strong 30 years total, with architecture-level ownership at ERGOS, D+H, RSM, SmarTek21, and Rackspace — private cloud, hybrid infrastructure, Citrix platforms, RPA/DevOps infra, and full-stack AWS/Azure/GCP. |
| Assess & align business + technical strategy with customer needs | Strong Core of the Rackspace advisory role: discovery workshops, Capex vs. Opex TCO modeling, migration wave planning, and executive business cases across energy, healthcare, insurance, financial services. |
| Excellent oral/written communication; presentation & workshop leadership across SME → executive | Strong Author of 14 pursuit briefs and many SOWs; direct C-suite relationships at D+H and RSM; workshop facilitation across dozens of engagements; public writing on Substack and the portfolio site. |
| Expert understanding of cloud-native patterns & Well-Architected best practices | Strong Hands-on with the AWS Well-Architected Framework (6 pillars) and MontyCloud-driven WAFR engagements producing credit-maximizing remediation plans; serverless/IaC-first architecture on every recent build. |
| Ability to travel up to 25% | Confirm Not addressed in resume/LinkedIn — have a direct, comfortable answer ready (remote-based, travel-ready). |
| Preferred: HA / fault-tolerant architectures | Strong Multi-region/HA design experience embedded in Well-Architected reviews; digital-twin dependency-graph simulation work explicitly modeling failure/6R disposition scenarios. |
| Preferred: IT compliance frameworks (PCI, HIPAA, GDPR, security) | Strong HIPAA, SOX, FFIEC, OCC/FDIC exposure managing 20+ regulated bank/healthcare clients at D+H; built a governance platform scanning code against 10 frameworks including HIPAA, NIST AI RMF, ISO 42001, EU AI Act, SOC2, FedRAMP. |
| Preferred: pre-sales or internal strategic roadmap influence | Strong This is the central thread of the last 4 years — pre-sales solution architecture is the day job, not an adjacent skill. |
| Preferred: AWS SA Professional / DevOps Professional / Specialty certs | Partial Have: AWS DevOps Professional, AWS Solutions Architect Associate, AWS Cloud Practitioner. Gap: no SA Professional or Specialty cert yet — name this directly and pair it with the depth of hands-on WAFR/MAP/OLA delivery as the offsetting proof point. |
| Preferred: deep domain expertise in App Dev, Data, or DevOps | Strong App Dev: agentic AI systems shipped to production in days. Data: BigQuery/pgvector pipelines, forecasting (LightGBM, Prophet). DevOps: Scrum Master roles, CI/CD, IaC across three clouds. |
| Preferred: industry vertical expertise (FinTech, Healthcare, Oil & Gas) | Strong Financial services (D+H, RSM — OCC/FDIC/FFIEC regulated banks), Healthcare (clinical portfolio migration analysis, D+H healthcare clients), Energy (AWS strategic account engagement, datacenter-to-cloud TCO for energy sector customer). |
Situation: Onica/Rackspace's Public Cloud Advisory practice needed a principal architect who could own the full pre-sales lifecycle across verticals.
Action: Personally authored many SOWs and led deep-dive architecture sessions across healthcare, financial services, telecom, retail, energy, and government.
Result: $57M+ combined opportunity value, 10 SOWs closed on 14 named pursuits.
→ 14 anonymized engagement briefsSituation: Customers needed AWS partner-funded assessments to unlock credits and build migration business cases.
Action: Delivered WAFR via MontyCloud with credit-maximizing remediation plans, OLA via Evolve (Microsoft/SQL Server/Oracle licensing), MAP Assess via Flexera Cloudscape, and MAP Migrate/App Modernization via Tidal Cloud.
Result: Reusable solution patterns across 6+ verticals; direct peer coaching on program delivery.
→ Cloud advisory engagement detailSituation: CSA peers were spending 4+ hours per account on manual pre-call research.
Action: Designed and shipped an agentic pre-sales intelligence tool producing 13-section company briefings in ~8 minutes from a single input.
Result: Deployed practice-wide, eliminating that research overhead for every CSA on the team — directly answers "raise everyone else's game," not just your own numbers.
→ Pre-Sales Intelligence Agent case studySituation: A healthcare client needed a 408-VM, 36-application portfolio assessed for cloud migration disposition.
Action: Architected a multi-agent AWS Bedrock/Claude pipeline with 22 deterministic governance rules to eliminate hallucinated recommendations.
Result: Full assessment in under 5 hours for $24 in AI compute — a discovery timeline that used to take weeks, with provenance-tagged recommendations a customer's compliance team could trust.
→ Migration analysis platform architectureSituation: D+H's Citrix Private Cloud customers (banks + healthcare) faced multiple OCC/FDIC/FFIEC/HIPAA audit and exam events per year.
Action: Acted as virtual CIO / cloud services architect for the book of business, going on record for exam certification and remediation.
Result: $12M in renewal TCV over 18 months on a 20+ client, $4.5M book — directly relevant to Caylent's "compliance frameworks" preferred qualification.
Situation: JD asks for blogs, white papers, webinars, and direct evangelism of AWS.
Action: Independently run AI Pathfinder — architecture write-ups, live demos, and a Substack publication documenting real builds, costs, and trade-offs.
Result: 25+ published solution case studies with working code and architecture diagrams — proof this is a habit, not a one-off ask.
→ Full portfolio (25+ solutions)Multi-agent pipeline on AWS Bedrock + Claude Sonnet analyzing a 36-app / 408-VM healthcare portfolio. 22 deterministic governance rules validate every agent output before it's trusted — the same "agents propose, rules/humans approve" pattern Accelerate™ uses for remediation. $24 total AI compute, 4.9-hour runtime, zero hallucinated numeric outputs.
→ Solution detail · Architecture5-agent Bedrock swarm plus 2 MCP servers running on ECS Fargate for a HIPAA-compliant healthcare platform generated entirely from spec. AWS MCP Server is literally one of the four pillars Caylent names for Accelerate™ — I've already shipped MCP servers in production, not just read the spec.
→ Solution detail · ArchitectureAgentic tool-use system (Claude, live APIs) producing a 13-section company brief in under 10 minutes, replacing 4+ hours of manual research — deployed team-wide at Rackspace. Direct proof of "agents doing the highest-volume, lowest-differentiation work so humans focus elsewhere," Accelerate's core value prop.
→ Solution detail · Architecture10-framework compliance scanner enforcing 5 human-approval gates before an AI system reaches production. This is my closest built analog to Accelerate's "guardrailed remediation" model — I already design the checkpoint/audit-trail layer that sits around autonomous agent actions.
→ Solution detail · ArchitectureFull Lambda + DynamoDB serverless deployment (5 CloudFormation stacks, 17 API routes) built as a cloud-adapter port of an existing Azure system — zero forked business logic. Direct evidence of designing serverless boundaries around existing application logic rather than a rewrite.
→ Solution detail · ArchitectureAWS Lambda-based simulation engine running 5 AI simulations (wave rehearsal, blast radius, right-sizing, TCO) across 1,053 servers. Good example of choosing Lambda for bursty, event-driven analysis work rather than always-on compute.
→ Solution detail · ArchitectureStep Functions-orchestrated ETL pipeline with PHI masking as part of a HIPAA-compliant serverless architecture — shows judgment on where Fargate (long-running agent swarm) is the right call versus where Step Functions/Lambda (bounded, auditable steps) is correct.
→ Solution detailDocumented migration PostgreSQL → Cosmos DB → back to PostgreSQL after a hot-partition problem hit at 5.9M documents and the fix would've cost $394/month with no benefit. This is the single best story for a "walk me through a data platform migration decision" question — real numbers, real reversal, six documented lessons.
→ Solution detail · Architecture8 years of METAR + radiosonde data fused in BigQuery with a spatial boost via ST_DISTANCE; 6 scikit-learn models trained on 44K+ observations. Directly analogous to Redshift Serverless + Athena lakehouse patterns — translate BigQuery vocabulary to Redshift/Glue/Lake Formation on the fly.
→ Solution detail · ArchitectureETL + SLM-routed query engine over 1.6M+ records with 3 query strategies (vector, numeric, hybrid) and deterministic fast paths that bypass AI inference entirely when not needed — relevant if the interview goes into vector search / RAG-in-a-lakehouse territory.
→ Solution detail · ArchitectureLive 30-day telemetry collection across 1,053 servers / 4 datacenters, dependency graph with 174 edges, and an 8-rule 6R disposition engine producing wave-rehearsal, blast-radius, and TCO simulations. This is a working tool version of the exact WAFR/MAP discovery work described in the JD.
→ Solution detail · ArchitectureWAFR via MontyCloud with credit-maximizing remediation plans; MAP Assess via Flexera Cloudscape; MAP Migrate & App Modernization via Tidal Cloud; OLA via Evolve for Microsoft/SQL Server/Oracle licensing. Dozens of pursuits, $57M+ combined TCV, many SOWs authored.
→ Advisory engagement detail · Pursuit librarySame governance platform ported to AWS and Azure with zero forked business logic (Cosmos DB → DynamoDB, Key Vault → Secrets Manager, Azure AI → Bedrock, all invisible to handlers) — a concrete portability/reliability Well-Architected story with a diagram to point to.
→ Solution detail · Architecture36 apps, 408 VMs, full migration disposition analysis for $24 in AI compute — a discovery timeline that used to take weeks of manual work.
→ Solution detailIdentified a hot-partition problem whose "fix" cost $394/month with zero benefit, migrated back to PostgreSQL, and documented six lessons — a real cost-optimization reversal, not just a savings number.
→ Solution detail25+ deployed solutions across AWS, Azure, and GCP running under $100/month combined — a defensible answer if asked to reason about running cost-efficient production systems at small scale before they justify Reserved/Savings Plans conversations.
→ Platform overviewPre-sales intelligence agent eliminated 4+ hours of manual research per account, deployed team-wide — the same "engineer time reclaimed" framing Caylent uses for Accelerate's remediation-time savings.
→ Solution detailpark_aggregates workload never needed a NoSQL round-trip at all; that's the more credible answer than a vendor-preference claim.Currently hold DevOps Professional + SA Associate, not SA Professional or a Specialty cert. If asked directly: acknowledge it, then pivot to the depth of hands-on delivery (WAFR, MAP, OLA, multi-region Well-Architected reviews) as evidence the practical bar is already met — and state intent to sit for SA Pro if it matters for the role.
Rackspace/Onica is an AWS partner, but the org structure differs from a pure-play AWS consultancy like Caylent. Frame it as: same motion (pursuit team collaboration, SOW authorship, AWS program delivery), different org wrapper — and that the muscle memory transfers directly.
Not addressed anywhere in resume/LinkedIn. Have a direct, confident answer ready before the call — don't let this surface as a surprise.