// Resume data — single source of truth const RESUME = { name: "Trent Bakow", role: "Engineering Manager · AI Platform", location: "American Fork, UT", email: "trentbakow@gmail.com", phone: "+1 (208) 863-5128", github: "DSO-TB", linkedin: "https://linkedin.com/in/trentbakow", pitches: [ "Engineering manager and AI platform builder. I ship production AI systems, lead the teams doing it, and keep the infrastructure underneath it all from falling apart.", "91% deploy time reduction. $75K saved. Production AI shipped. I've run the infra work — now I run the team, and I still write the hard stuff.", "I architect AI-powered platforms, integrate foundation models into real operational workflows, and manage the engineers building what comes next.", "AWS-native engineering manager. Cloud migrations and platform automation got me here — production AI systems, agentic tooling, and LLMOps are where I'm going.", ], // Headline impact metrics — hover for full context metrics: [ { value: "6+", label: "AI systems shipped", detail: "Production AI platforms, agentic tools, and multimodal pipelines — spanning independent products, internal tooling, and a hackathon win." }, { value: "$75K", label: "Annual cost savings", detail: "60% observability cost reduction through strategic AI and platform tooling decisions — full vendor migration, zero incident impact." }, { value: "91%", label: "Deploy time reduction", detail: "24h → 15 min via Python/Go automated provisioning pipeline. Immediately unblocked 200+ engineers." }, { value: "100%", label: "Uptime through cutover", detail: "Designed HA multi-region DR + VPN architecture for Azure→AWS enterprise migration. Zero downtime windows." }, { value: "65%", label: "Investigation time cut", detail: "End-to-end audit logging platform on MSK + OpenSearch. Compliance-ready, customer-visible, zero blind spots." }, { value: "3,000+", label: "Schemas migrated", detail: "GCP cloud migration with 100% data integrity. Led 6-person cross-functional team from runbooks to cutover." }, { value: "40%", label: "Perf gain, −20% cost", detail: "Couchbase + Elasticsearch migration to AWS. Zero downtime. Faster queries and lower spend, simultaneously." }, { value: "95%", label: "Deploy time at Dexi", detail: "5–6 hours → 10–15 minutes. Built Ansible automation for EKS cluster provisioning from the ground up." }, ], // AWS services — hex grid. level = depth of production use (1–5) awsServices: [ { code: "ECS", name: "Elastic Container Service", level: 5, desc: "Production workloads at JobNimbus and Dexi. Owned service definitions, task IAM, and blue/green deployments via CodeDeploy." }, { code: "EKS", name: "Elastic Kubernetes Service", level: 5, desc: "Ansible-driven cluster automation cut deploy time 95% at Dexi. Ran ArgoCD-backed GitOps pipelines at scale." }, { code: "MSK", name: "Managed Streaming for Kafka", level: 4, desc: "Built replayable data pipelines for the audit logging platform at JobNimbus. Schema registry, IAM auth, consumer group management." }, { code: "OpenSearch", name: "OpenSearch / Elasticsearch", level: 5, desc: "Migrated legacy Elasticsearch to OpenSearch with 100% retention via replayable MSK pipelines. Query tuning, ILM, snapshotting." }, { code: "RDS", name: "Relational Database Service", level: 5, desc: "Zero-downtime Aurora v1→v2 migration on production databases. Bucardo replication + custom PL/Perl compatibility rewrites." }, { code: "IAM", name: "Identity & Access Management", level: 5, desc: "Designed auth infrastructure for enterprise cloud migrations. SCPs, permission boundaries, role chaining, and cross-account access patterns." }, { code: "R53", name: "Route 53", level: 4, desc: "Multi-region failover routing, weighted A/B splits, and private hosted zones for VPN-scoped services. Health-check-driven DR." }, { code: "VPC", name: "Virtual Private Cloud", level: 5, desc: "Owned end-to-end network architecture for cloud migrations. Transit gateways, cross-region peering, subnet design, and multi-region DR topologies." }, { code: "CF", name: "CloudFront", level: 4, desc: "Edge caching + WAF for customer-facing applications. Signed URLs for tenant isolation, cache behavior tuning, and origin failover." }, { code: "S3", name: "Simple Storage Service", level: 5, desc: "Bucket policies, cross-region replication, and lifecycle rules. Backing store for backups, compliance audit logs, and CI/CD artifacts." }, { code: "λ", name: "Lambda", level: 4, desc: "Event-driven automations: cost reporting, SNS alert handlers, infra orchestration triggers. Go and Python runtimes." }, { code: "IaC", name: "Infrastructure as Code", level: 5, desc: "Terraform and OpenTofu modules across every team I've worked on. Default platform-IaC reviewer, module author, and standard-setter." }, { code: "Bedrock", name: "Bedrock", level: 5, desc: "Primary LLM runtime across production AI systems — model selection, inference config, prompt routing, and cost controls. Used in AutoRemediate, VectorCore, AffectOS, and Conversational Search." }, { code: "DynamoDB", name: "DynamoDB", level: 4, desc: "Session state, tenant metadata, and event records across multiple SaaS platforms. Designed key schemas for high-throughput access patterns and TTL-based expiry." }, ], // Career timeline — each bullet is a delivered outcome timeline: [ { year: "2022 — Now", yearShort: "2022", company: "JobNimbus", title: "Sr DevOps Eng → Eng Manager", bullets: [ { metric: "Eng Manager", text: "Promoted to Engineering Manager Feb 2026 — own headcount, performance management, and technical mentorship across the team." }, { metric: "Team growth", text: "Led hiring and onboarding for the engineering team — grew team capabilities while maintaining operational excellence." }, { metric: "Standards", text: "Built engineering culture and technical norms — 1:1 cadence, growth frameworks, architecture review standards." }, { metric: "Hands-on", text: "Maintained hands-on technical ownership alongside management — drive architecture decisions and stay in the critical path on complex work." }, { metric: "AI shipped", text: "Shipped production AI systems: conversational interfaces for internal technical workflows and auto-remediation pairing LLM reasoning with infrastructure automation." }, { metric: "AI outcomes", text: "Delivered significant cost reductions and deployment efficiency gains through AI-enabled infrastructure work." }, { metric: "$50–75K/yr", text: "Drove 60% observability cost reduction — led full vendor evaluation, selection, and platform migration with zero incident impact." }, { metric: "100% uptime", text: "Maintained zero downtime through Azure→AWS enterprise migration — designed HA multi-region DR and VPN architecture from first principles." }, { metric: "Core network", text: "Architected VPC, Transit Gateway, and R53 failover routing for cloud migration. Owned IAM auth strategy across all migrated services." }, { metric: "65% faster", text: "Built end-to-end audit logging platform on MSK + OpenSearch — cut security investigation time 65% and enabled compliance reporting." }, { metric: "+40% / −20%", text: "Migrated Couchbase and Elasticsearch to AWS with zero downtime — query performance up 40%, infrastructure cost down 20%." }, { metric: "Full retention", text: "Modernized legacy Elasticsearch with replayable MSK data pipelines — zero data loss, improved query latency, and automated ILM." }, ], }, { year: "2021 — 2022", yearShort: "2021", company: "Reliaquest", title: "DevOps Engineer II", bullets: [ { metric: "91% faster", text: "Designed Python/Go provisioning pipeline from scratch — reduced deploy time from 24h to 15 min and immediately unblocked 200+ engineers." }, { metric: "Zero downtime", text: "Executed Aurora v1→v2 migration on critical production databases using Bucardo replication and custom PL/Perl compatibility rewrites." }, { metric: "Platform lead", text: "Led enterprise Snowflake integration technical evaluation — primary technical voice shaping the company's data platform direction." }, { metric: "3 regions", text: "Architected disaster recovery across US-East, US-West, and EU — 100% data retention policy with defined RTO and RPO targets." }, { metric: "Incident cmd", text: "War-room incident commander for production outages — owned real-time diagnosis, resolution coordination, and postmortem delivery." }, ], }, { year: "2019 — 2021", yearShort: "2019", company: "Dexi.io", title: "Implementation Eng → DevOps I → DevOps II", bullets: [ { metric: "3,000+ schemas", text: "Led 6-person cross-functional team migrating 3,000+ customer schemas to GCP — 100% data integrity, custom runbooks, zero missed deadlines." }, { metric: "95% faster", text: "Built Ansible automation for EKS cluster provisioning — reduced deploy time from 5–6 hours to 10–15 minutes across all environments." }, { metric: "Stack author", text: "Architected Kafka + Ceph + ELK + Nginx from the ground up — streaming, distributed storage, and full-stack observability." }, { metric: "15% revenue", text: "Primary technical contact for Fortune 500 accounts representing 15% of company revenue as an Implementation Engineer." }, { metric: "80% faster", text: "Cut on-prem upgrade cycle from 1–2 days to 4–5 hours via automated deployment tooling." }, { metric: "+75% capacity", text: "Expanded engineering team throughput through structured mentoring programs, pairing sessions, and runbook initiatives." }, { metric: "400+ machines", text: "Managed 400+ physical and virtual machines — sole infrastructure owner across all engineering teams during growth phase." }, ], }, ], // Currently exploring current: [ { tag: "GenAI", note: "Production RAG patterns" }, { tag: "MCP", note: "Server development" }, { tag: "Agentic", note: "Multi-agent infra" }, { tag: "Vector DBs", note: "Retrieval architectures" }, ], // Projects — AI systems built projects: [ { name: "AutoRemediate", badge: "AI-Driven CI/CD", desc: "AI-driven CI/CD and infrastructure management platform for ECS workloads. Integrates AWS Bedrock and MCP to detect deployment failures, reason over logs and service state, and trigger targeted remediation — all without human intervention. Ops teams get a conversational interface to inspect, roll back, or override from natural language.", tags: ["AWS Bedrock", "MCP", "ECS", "Terraform", "Docker"], }, { name: "VectorCore", badge: "Product", desc: "AI-native SaaS platform with a multi-agent QA pipeline, full LLM evaluation framework, and tenant-scoped vector search with RAG retrieval. Built a custom eval harness to benchmark model outputs across quality, groundedness, and latency — with per-tenant embedding strategies and full multi-tenant isolation on AWS.", tags: ["Multi-agent", "RAG", "Vector Search", "LLM Evals", "ECS", "RDS", "DynamoDB", "API Gateway"], }, { name: "AffectOS", badge: "AI Emotional Analytics", desc: "Multimodal emotional intelligence platform that fuses real-time facial expression analysis, vocal prosody modeling, and language understanding into composite per-emotion scores. Layered a conversational AI interface on top — Bedrock + MCP-backed, surfacing live behavioral and operational data through natural language behind enterprise SSO.", tags: ["Multimodal AI", "LangChain", "MSK", "Lambda", "OpenSearch", "Bedrock", "MCP", "Okta", "Node.js"], }, { name: "Conversational Search", badge: "Hackathon Win", desc: "Natural-language query engine over OpenSearch — users describe what they want in plain English and a Bedrock-powered LLM generates, executes, and iteratively refines Elasticsearch DSL in real time. Collapses the gap between domain experts and raw search infrastructure. No query syntax required.", tags: ["AWS Bedrock", "OpenSearch", "Python", "NLP"], }, ], // Capabilities — full stack from model to metal stack: { "AI Engineering": [ "Frontier Models (Claude, GPT, Bedrock)", "LangChain · Node.js + Python", "MCP Servers", "Multi-agent Systems", "RAG / Vector Search", "LLM Evaluation & Evals Frameworks", "Prompt Engineering", "AI Observability (Langfuse, Opik, LangSmith)", "AI Safety & Guardrails", "Multimodal AI (voice, vision, language)", ], "Platform & Cloud": [ "AWS — ECS, EKS, Lambda, Bedrock, MSK", "RDS, DynamoDB, OpenSearch, S3, CloudFront", "R53, VPC, ACM, SSM, Kinesis", "Terraform · OpenTofu · Ansible", "Kubernetes · ArgoCD · CodeDeploy", "GitHub Actions · GitLab CI", "Cloudflare Pages & Access", ], "Application & Data": [ "React · Vite · Astro", "Node.js · Python · Go · Bash", "PostgreSQL · DynamoDB · Aurora", "OpenSearch · Kafka / MSK · Ceph", "Multi-tenant SaaS patterns", "Row-level security · Tenant isolation", ], "Auth & Observability": [ "Okta · Clerk · Cloudflare Access", "OAuth / SSO / OIDC", "Datadog · Grafana · Splunk", "ELK Stack · Portkey", "Distributed tracing · APM", "LLM cost monitoring", ], }, education: [ { degree: "B.S. Information Technology", focus: "Network Administration & Security", school: "Utah Valley University", years: "" }, ], certifications: [ { code: "SAA", name: "AWS Certified", title: "Solutions Architect", level: "Associate", img: "aws-saa-badge.png", issuer: "Amazon Web Services", url: "https://aws.amazon.com/certification/certified-solutions-architect-associate/", }, ], }; window.RESUME = RESUME;