Daniel Parker

• Led architecture and delivery of a multi-tenant AI revenue-operations platform built with React, Next.js, FastAPI, LangGraph, PostgreSQL, pgvector, Redis, and AWS, supporting 18 client workspaces and 75+ configurable AI and automation workflows.
• Built inbound and outbound voice agents for lead qualification, scheduling, customer support, campaign follow-up, and after-hours coverage, processing approximately 4,500 calls per month through Vapi, Deepgram, OpenAI, Anthropic, ElevenLabs, and Twilio.
• Introduced a provider-independent speech and model layer across Deepgram, Amazon Transcribe, ElevenLabs, Amazon Polly, OpenAI, Anthropic, and Amazon Bedrock, routing by latency, quality, availability, and cost with automatic failover.
• Connected voice and chat agents with HubSpot, Salesforce, and GoHighLevel for customer context, lead scoring, CRM updates, meeting scheduling, confirmations, and qualified-call transfers.
• Improved grounded-answer accuracy by 24% with permission-aware RAG over websites, pricing, policies, campaign history, and sales documentation using pgvector, OpenSearch, metadata filtering, reranking, citations, and confidence-based escalation.
• Reworked lead-management automation around EventBridge, SQS, Lambda, n8n, idempotent APIs, retry policies, audit logs, and approval gates, reducing repetitive work by 61% and average response time from 26 minutes to under three minutes.
• Standardized deployment, observability, and AI evaluation with Docker, ECS Fargate, Terraform, GitHub Actions, CloudWatch, OpenTelemetry, Langfuse, and Sentry; built 450+ test conversations, added safeguards for high-risk behavior, and mentored four engineers.

Technology: React · Next.js · FastAPI · LangGraph · PostgreSQL · pgvector · Redis · OpenSearch · OpenAI · Anthropic · Amazon Bedrock · Vapi · Deepgram · ElevenLabs · Twilio · AWS · Docker · ECS Fargate · Terraform · OpenTelemetry · Langfuse

• Delivered supplier onboarding, catalog management, wholesale ordering, retailer accounts, payments, inventory visibility, and order tracking with React, TypeScript, FastAPI, PostgreSQL, Redis, and AWS for approximately 9,000 retailers, 1,200 suppliers, and 620,000 listings.
• Designed personalized recommendation services with collaborative filtering, PyTorch ranking models, product embeddings, behavioral data, and Amazon Personalize experiments, increasing recommendation click-through rate by 15% and average order value by 7%.
• Rebuilt product discovery with Elasticsearch, Amazon OpenSearch Service, synonym expansion, behavioral ranking signals, learning-to-rank, Pinecone, and OpenAI embeddings, reducing zero-result searches by 22%.
• Automated product classification, attribute extraction, supplier-data normalization, duplicate detection, and description generation across approximately 140,000 monthly catalog updates, cutting manual review effort by 46%.
• Trained XGBoost and neural-network forecasting models using order history, seasonality, promotions, pricing, supplier lead times, and category trends, reducing forecast error by 14% and stockouts by 17%.
• Productionized ML and generative-AI services with SageMaker, FastAPI, ECS, Lambda, Airflow, Step Functions, Docker, MLflow, and CloudWatch, maintaining 99.9% availability and improving inference latency by 36%; also delivered a GPT-3.5 Turbo support pilot that raised schema-valid outputs from 71% to 88%.

Technology: React · TypeScript · Python · FastAPI · PostgreSQL · Redis · PyTorch · XGBoost · Amazon Personalize · Elasticsearch · OpenSearch · Pinecone · OpenAI embeddings · SageMaker · AWS · Airflow · MLflow

• Shipped 11 responsive web applications and SaaS products with React, TypeScript, Node.js, Python, Django, PostgreSQL, and AWS for professional services, retail, logistics, and business operations clients.
• Created 35+ reusable REST API endpoints for authentication, accounts, payments, scheduling, document processing, notifications, and reporting; integrated Stripe, Salesforce, Twilio, Google Maps, and logistics platforms to accelerate client integrations and reduce development effort.
• Developed a multi-tenant operations platform with role-based access control, configurable workflows, reporting dashboards, audit histories, and customer self-service capabilities for more than 2,400 business users.
• Modernized four legacy applications into modular cloud-hosted services using Docker, AWS EC2, RDS, S3, Nginx, automated database migrations, and GitHub Actions, increasing deployment frequency from biweekly to three or four releases per week.
• Improved performance and reliability through Jest and Pytest automation, SQL optimization, caching, structured logging, monitoring, and root-cause analysis, reducing average API response time by 41% and production incidents by 29%.

Technology: React · TypeScript · Node.js · Python · Django · PostgreSQL · AWS · Docker · EC2 · RDS · S3 · GitHub Actions · Jest · Pytest