Skills
- Cloud Foundations: AWS compute, storage, IAM, VPC, Lambda, EventBridge, CloudFront, API Gateway
- AI/ML Platform Adjacent: Titan Text Embeddings v2, retrieval-augmented generation (RAG), vector search, chunking strategies, similarity scoring
- Data Ingestion & Orchestration: event-driven pipelines, presigned URLs, scheduled web scraping, DLQ handling
- Serverless Patterns: ingestion workflows, preprocessing, structured logs, latency monitoring, cold start mitigation
- Security Awareness: least-privilege IAM, encryption at rest/in transit, upload surface reduction, boundary enforcement
- Observability: CloudWatch metrics, latency tracing, structured JSON logs, p95 monitoring
- Web & Frontend: responsive layouts, reduced-motion respect, print styles, theme persistence, semantic landmarks
- Cost Discipline: lifecycle storage policies, scheduled cost snapshots, CDN caching
- Tooling & Practices: container packaging, CI workflows, object storage patterns, schema drift awareness
Skills in Practice
Serverless Architectures
Implemented Lambda + API Gateway patterns for event-driven workflows in a conversational RAG pipeline.
Embeddings & Vector Search
Used Titan Embeddings v2 + OpenSearch to enable semantic retrieval across multi-session chat context.
Event Scheduling
Configured EventBridge rules to trigger web scrapers and model-based recap generation on league cadence.
Cloud Security Awareness
Ensured least-privilege IAM roles, secret isolation, and public asset policy hardening on S3 static hosting.
Model Prompt Engineering
Structured prompts for consistency, hallucination mitigation, and domain-specific output formatting.
Monitoring & Observability
Used CloudWatch logs/metrics to diagnose throughput issues and iteration cadence during model testing.
Education & Programs
AWS Cloud Institute • Applied cloud architecture, serverless design, AI platform workflows
Certifications
- AWS Certified Cloud Practitioner (2025)
- AWS AI Practitioner (2025)
- AWS Machine Learning Engineer – Associate (in progress)
Graduate, AWS Cloud Institute
What I'm Learning Now
Continuous Growth
- Preparing for AWS Machine Learning Engineer – Associate (MLA-C01)
- Retrieval quality evaluation and scoring thresholds
- Embedding dimension trade-offs for domain-specific semantics
- Model cost analysis and inference latency controls
- Feature pipeline design and reproducibility patterns
- Vector index growth management and refresh strategies
- Batch vs. streaming ingestion for ML workloads
Projects
Conversational RAG Pipeline on AWS
Built a serverless Retrieval-Augmented Generation system enabling conversational Q&A over private documents using Titan Text Embeddings v2 and OpenSearch Serverless. Ingestion pipeline handles chunking, metadata tagging, and DLQ retries. Query path emphasizes business-context–aware retrieval and latency control.
Outcome: Reduced time spent searching institutional knowledge- S3 ingestion with EventBridge triggers
- Lambda for chunking and embedding generation
- Titan Embeddings v2 for vector representation
- OpenSearch vector index for semantic retrieval
- API Gateway inference endpoint
- Presigned URL upload boundaries
- Least-privilege IAM roles
- DLQ for ingestion failures
- CloudWatch logs for latency and token throughput
Fantasy League Companion (Sleeper + Bedrock)
Built a league companion that ingests fantasy football data from Sleeper, aggregates daily NFL news via EventBridge-triggered Lambda web scrapers, and prompts a Bedrock model to produce weekly recaps, power rankings, and matchup previews. Focused on structured prompt formatting and data freshness.
Outcome: Increased league engagement with timely, data-aware summaries- EventBridge schedules web scraping Lambdas for NFL news
- API calls to Sleeper for league statistics and rosters
- Structured prompt templates for consistent outputs
- Aggregation pipeline normalizes scoring and rankings
- Presigned URLs isolate upload surfaces
- CloudWatch logs trace execution and failures
Currently extending to surface trend deltas and injury implications.
Static Resume Site on AWS (S3 + CloudFront)
Designed and deployed a fast, responsive resume website hosted on S3 with CloudFront caching. Implemented correct MIME type configurations, public-read bucket policies, and accessibility affordances including skip links, reduced-motion support, keyboard focus rings, and semantic landmarks. Added dark/light theme persistence via localStorage and system preference detection.
Outcome: Improved recruiter scan efficiency and site performance- S3 static hosting with correct bucket policy boundaries
- CloudFront distribution with edge caching
- Dark/light mode theme persistence
- Reduced-motion preference support
- Skip-to-content and semantic aria landmarks
- Print stylesheet for recruiter workflows
Transitioning into cloud-based ML platform support, leveraging prior experience in ambiguity resolution, inventory accuracy, and structured onboarding.
Professional Experience
Area Sales Manager
- Prospected and onboarded new accounts while managing a large existing portfolio across a wide geographic territory.
- Drove ~40% growth in total case sales during summer 2023 by identifying operational bottlenecks and improving ordering cadence.
- Exceeded 70% in total brand sales, contributing to category adoption and supply alignment.
- Reduced customer churn risk by translating ambiguous product requirements into repeatable ordering workflows.
- Won two separate performance promotions based on measurable growth and account expansion.
Fulfillment Operations Manager / FSL Specialist
- Managed inventory accuracy and order fulfillment while coordinating with leadership on experimental operational procedures.
- Oversaw Apple partnership onboarding, including asset registration, SOP interpretation, and training new staff on partner workflows.
- Served as test market for new operational processes prior to nationwide rollout, providing structured feedback on scalability and failure modes.
- Trained new hires on complex SOPs, improving consistency and reducing operational defects across distributed teams.
- Recognized by national leadership as one of four specialists to exceed KPIs in consecutive quarters.
Stay-At-Home Parent
- Maintained household logistics while balancing competing time-sensitive priorities.
- Developed task batching, scheduling discipline, and lightweight documentation habits.
- Used flexible availability windows for independent study of cloud services, AI workflows, and platform fundamentals.
About
I build practical cloud and ML tooling that improves delivery speed and reduces cognitive overhead for teams. I value simplicity, observability, and continuous refinement.
Contact
Seeking opportunities developing cloud infrastructure for ML workloads.
Email Me