Inference Scheduling Service (Rudi)

• Co-architected and developed Rudi, a Rust-based Bedrock inference scheduling service handling 1000+ TPS; governs timing and ordering of inference requests from FES to foundation models — implementing concurrency-per-variant enforcement, priority-based queuing with weighted round-robin scheduling, request throttling/load shedding, and deferred capacity allocation enabling Provisioned Throughput V2 without hard-allocating capacity
• Built on single-threaded Tokio scheduling engine with MPSC/oneshot channel patterns for microsecond-level scheduling decisions; deployed across all Bedrock regions

Priority Queue Migration

• Implemented two-phase zero-downtime migration from legacy 4-value (0,1,2,3) to standardized 7-tier priority system (P5–P100), with bidirectional session token normalization handling values 0–150 for rollback compatibility
• Built configuration-driven priority weights, AppConfig/Rust fallback configs, and capacity allocation constraints; deployed across Beta, PreProd, and Prod with zero incidents over 6-week rollout enabling 2 new revenue tiers (Premium OD, Best Effort OD)

Quality of Service (QoS)

• Implemented QoS tier mapping (RudiPriority → QoS 0/1/10) in schedule responses and forwarding logic for Anthropic models (Claude Sonnet, Haiku, Opus); added preemptable flag in capacity constraints and AppConfig-based model QoS detection
• Built unified priority assignment avoiding separate QoS vs. non-QoS code paths; updated capacity allocator to deduct preemptable consumption only for QoS-supported models

RAMA Classification Consolidation

• Led 4-team consolidation expanding from 2-value to 10-classification system (PTv2, Priority Access, OnDemand, Flex, Batch); implemented fail-closed exception throwing in Rudi and FES for unknown classifications with SEV2 alarms
• Built thick client with AppConfig-based cached overrides (50+ account-level imports), shadow mode validation framework, and session token migration including RAMA classification for request lifecycle consistency

ServiceTier API

• Implemented ServiceTier-to-RudiPriority mapping with configuration-driven rules engine (service_tier.json, 15+ rules) supporting FLEX/PRIORITY tiers and RAMA BEST_EFFORT integration; built dual-operation mode with RequestType fallback and feature flags for gradual rollout

Leader-Follower & Game Day

• Implemented leader-follower architecture with DynamoDB coordination, request forwarding, and broadcast mechanisms; automatic failover recovery under 10 seconds
• Built and executed 27 Game Day failure scenarios (routing, leader election, capacity tracking, peer communication); identified and fixed 5 critical edge cases including session token priority mismatches, TTL recovery, and ALB cookie validation

Operations & Full-CD

• Resolved 800+ tickets; created 30+ composite alarms reducing false positives by 70%; reduced MTTR by 60% through variant-level monitoring, priority fairness alarms, and cache error metrics
• Enabled Full-CD for AppConfig, Canary, and Service pipelines with 20+ rollback alarms and ECS circuit breakers; drove region expansion and 10+ model launches (Claude Sonnets, Haikus, Opus, Amazon Nova family) resolving GMDS fallback, health check, and AZ blockers

Accuracy Scorecard Framework

• Built Phase 2 evaluation pipeline across 5 ISV connectors (SharePoint, WebCrawler, Confluence, GoogleDrive, S3) and 5 document types (HTML, PDF, DOCX, PPTX, CSV) measuring Correctness (LLM-based), CitScore (citation validation), and Retrieval metrics (Recall/Precision @1/5/10) with automated CloudWatch emission and QuickSight dashboards
• Implemented GoogleDrive test corpus (115K Finance FIQA documents, 300 queries) achieving 99.3% retrieval recall@1; built SharePoint multi-document test sites with M365 token auth; created WebCrawler Amplify CDK infrastructure with HTML conversion scripts for multi-modal content (tabular, images, audio); achieved 60% reduction in manual testing via automated canary infrastructure

Data Ingestion Pipeline

• Implemented integration between ProductivityIngestionService and PreProcessor service handling UPSERT workflows, GetResource, and delete events; built IngestionNotificationLambda closing failure-scenario gaps and refactoring EventIngestionQueue model
• Implemented dynamic attribute mapping for Kendra index ingestion via Q Business BatchPutDocument, simplifying complex data transformations for downstream indexing

Console Development & Launch

• Led end-to-end development of AWS AppFabric Console from greenfield project, contributing to 75%+ of Console ORR tasks including pipeline setup, Cloudscape design system integration, localization, analytics, and security
• Implemented operational dashboards (client-side and server-side), Content Security Policy violation testing using Puppeteer, and CSAT/Aperture feedback integration
• Reduced console deep canary test runtime from 40 minutes to under 4 minutes while maintaining full test coverage
• Proposed and delivered console analytics strategy using Panorama for user behavior analysis, accessibility testing strategy, and Lighthouse security audits

PostureHub API Design & Development

• Led API design and development for PostureHub across FrontEndService and Core Observability teams, implementing 6 APIs: GetAppConfiguration, GetFinding, GetPosturePolicy, ListAppEntities, ListFindings, ListPosturePolicies
• Proposed and implemented ARN structure for PostureHub resources ensuring scalability and maintainability

AppServer & Third-Party Integrations

• Co-delivered AppServer before re:Invent maintaining 90%+ test coverage; built Fabric OAuth system ensuring message integrity for Asana, Slack, and G-Suite integrations
• Re-invented Salesforce audit log strategy handling both hourly and daily log intervals, implementing kill switch for large EventLogFile sizes and event-level pagination design
• Designed and implemented ListSheets API and Smartsheet strategy end-to-end, simplifying normalized schema and guiding performance testing
• Created automated weekly data extraction ETL Lambda pipeline from DynamoDB (Asana/Slack) to CSV for Business Intelligence team

IAM & Security

• Developed and released AWS AppFabric managed IAM policies (FullAccess & ReadOnly) end-to-end, coordinating cross-team reviews with AppSec, IAM, KMS, and documentation teams through MCM release process
• Onboarded Taj service for continuous API security testing, implementing automated security scanning workflows in CI/CD pipelines and production canaries
• Participated as Guardian for threat model evaluations across EndUserPush, PostureHub, and Transmission services

Cross-Team Leadership & Operations

• Mentored junior engineers, interns, and persistent team members; hosted office hours, conducted code reviews, and created comprehensive onboarding documentation
• Led JDK 8/11 to JDK 17 migration initiative within AppFabric, driving timeline discussions during Ops meetings

• Designed and implemented Partner Tag Customization feature for Amazon Chime, replacing <EXTERNAL> with customizable <PARTNER> tags for trusted subsidiaries, supporting multiple partners per conversation with feature flag rollback capability
• Proposed and demoed 3 rendering approaches; implemented scalable solution using UCBuzzExpress SDK supporting Web and Desktop clients with multi-language translation support
• Led urgent migration of AWS WorkDocs Console from Angular to Cloudscape within 3-month deadline, driven by a critical security vulnerability; set up React testing framework with Babel configuration
• Established greenfield project foundation including Polaris integration, internationalization support, and unit testing infrastructure

• Developed features for Kolibri, an open-source educational platform serving millions of learners worldwide, using Django, SQL, and VueJS
• Led cross-functional project delivery coordinating frontend and backend milestones; optimized database queries and API endpoints improving system performance

• Built quiz application used by 100s of students for English proficiency evaluation (HTML, CSS, JavaScript, PHP, MySQL)
• Developed parking space detection prototype using OpenCV, Keras/TensorFlow with 90% accuracy
• Improved real-time client portal UI efficiency by 70% using MVC architecture