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I’m Derrek Williams, a senior AI/ML and back-end engineer with 14+ years of experience building scalable enterprise applications, distributed data platforms, and production-grade AI systems. My work focuses on turning complex retrieval and generation needs into reliable, secure services—especially with RAG and agentic workflows—while keeping performance, cost, and latency tightly under control. I’ve designed and delivered secure AI retrieval services end-to-end, improved retrieval accuracy through hybrid search and reranking, and modernized high-volume back-end systems with event-driven architectures. I also build repeatable evaluation pipelines for LLM outputs (groundedness, citation accuracy, latency, and structured outputs) and mentor teams on architecture, API reliability, and secure AI development to help products ship faster with fewer regressions.…I’m Derrek Williams, a senior AI/ML and back-end engineer with 14+ years of experience building scalable enterprise applications, distributed data platforms, and production-grade AI systems. My work focuses on turning complex retrieval and generation needs into reliable, secure services—especially with RAG and agentic workflows—while keeping performance, cost, and latency tightly under control. I’ve designed and delivered secure AI retrieval services end-to-end, improved retrieval accuracy through hybrid search and reranking, and modernized high-volume back-end systems with event-driven architectures. I also build repeatable evaluation pipelines for LLM outputs (groundedness, citation accuracy, latency, and structured outputs) and mentor teams on architecture, API reliability, and secure AI development to help products ship faster with fewer regressions.

Derrek Williams

Back-End Developer, Full Stack Developer, AI Engineer, +2

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I’m Derrek Williams, a senior AI/ML and back-end engineer with 14+ years of experience building scalable enterprise applications, distributed data platforms, and production-grade AI systems. My work focuses on turning complex retrieval and generation needs into reliable, secure services—especially with RAG and agentic workflows—while keeping performance, cost, and latency tightly under control. I’ve designed and delivered secure AI retrieval services end-to-end, improved retrieval accuracy through hybrid search and reranking, and modernized high-volume back-end systems with event-driven architectures. I also build repeatable evaluation pipelines for LLM outputs (groundedness, citation accuracy, latency, and structured outputs) and mentor teams on architecture, API reliability, and secure AI development to help products ship faster with fewer regressions.…I’m Derrek Williams, a senior AI/ML and back-end engineer with 14+ years of experience building scalable enterprise applications, distributed data platforms, and production-grade AI systems. My work focuses on turning complex retrieval and generation needs into reliable, secure services—especially with RAG and agentic workflows—while keeping performance, cost, and latency tightly under control. I’ve designed and delivered secure AI retrieval services end-to-end, improved retrieval accuracy through hybrid search and reranking, and modernized high-volume back-end systems with event-driven architectures. I also build repeatable evaluation pipelines for LLM outputs (groundedness, citation accuracy, latency, and structured outputs) and mentor teams on architecture, API reliability, and secure AI development to help products ship faster with fewer regressions.

Available to hire

I’m Derrek Williams, a senior AI/ML and back-end engineer with 14+ years of experience building scalable enterprise applications, distributed data platforms, and production-grade AI systems. My work focuses on turning complex retrieval and generation needs into reliable, secure services—especially with RAG and agentic workflows—while keeping performance, cost, and latency tightly under control.

I’ve designed and delivered secure AI retrieval services end-to-end, improved retrieval accuracy through hybrid search and reranking, and modernized high-volume back-end systems with event-driven architectures. I also build repeatable evaluation pipelines for LLM outputs (groundedness, citation accuracy, latency, and structured outputs) and mentor teams on architecture, API reliability, and secure AI development to help products ship faster with fewer regressions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

Work Experience

Senior AI Backend Engineer at Nike

January 1, 2023 - Present

Architected a secure enterprise RAG platform using Python, FastAPI, Pinecone, PostgreSQL, and OpenAI/Anthropic models, cutting average product-information research time by ~48% across merchandising, marketing, and support. Built hybrid retrieval and reranking pipelines combining semantic search, keyword matching, metadata filters, and source prioritization to improve top-result relevance by ~31% and reduce unsuccessful searches by ~42%. Implemented strong security with row-level security, server-side authorization, tenant-aware filtering, and audit logging across 100% of document requests to maintain zero cross-domain exposure incidents. Orchestrated asynchronous agent workflows connecting product data, CMS platforms, and approval systems—reducing campaign content-prep time by ~58% and shortening review cycles by ~34% while preserving human publishing controls. Established automated LLM evaluation pipelines (retrieval relevance, citation accuracy, groundedness, latency, and structur

Full Stack Engineer & AI Researcher at Tech Consulting Group

January 1, 2020 - November 1, 2022

Developed a multi-tenant semantic search SaaS using Python, FastAPI, Pinecone, PostgreSQL, and OpenAI embeddings, improving relevant-result selection by ~27% and reducing zero-result searches by ~33%. Built reusable ingestion connectors for CMS, CRM, document repositories, and third-party APIs, reducing average client onboarding time by ~45% across multiple engagements. Implemented tenant-specific vector namespaces, PostgreSQL row-level security, and server-side authorization for multiple client environments to ensure complete data separation with zero cross-client access incidents. Productized an AI-assisted content workflow that generated and summarized customer-facing material from CRM and CMS data, reducing first-draft preparation time by ~52% and increasing weekly content throughput by ~36%. Standardized prompt templates, structured outputs, validation rules, caching, and API retry handling to reduce inconsistent model responses by ~30% and lower AI-related support issues by ~21%

Software Engineer at Google

March 1, 2018 - October 1, 2020

Designed an event-driven analytics architecture on Google Cloud using Pub/Sub, Cloud Functions, and BigQuery to process 8M+ application events per day while decoupling producers from downstream analytics consumers. Built near-real-time ingestion and transformation pipelines, reducing analytics data availability from ~3 hours to under ~12 minutes for supported product datasets. Hardened distributed processing by implementing idempotent consumers, schema validation, dead-letter handling, replay workflows, and automated alerting, improving successful event-processing rate to ~99.6% and reducing manual recovery effort by ~57%. Streamlined BigQuery table partitioning, clustering, and transformation logic to lower targeted query costs by ~31% and improve average analytical query execution times by ~37%. Instrumented A/B testing pipelines with assignment validation, data freshness monitoring, and outcome reconciliation, cutting experiment-data preparation time by ~44% and identifying broken

Full Stack Developer at Red Ventures

January 1, 2017 - February 1, 2018

Launched Node.js and Java personalization services supporting 4 consumer-facing digital experiences, reducing targeting-response latency by ~29% and enabling reusable offer-selection logic across multiple products. Refactored high-traffic REST APIs and SQL queries through indexing, query restructuring, and reduced database round trips, improving average endpoint response time by ~41% and lowering peak database load by ~27%. Accelerated A/B experiment delivery by separating targeting and assignment logic from individual applications, shortening experiment launch cycles by ~35% and improving consistency of user assignments. Introduced caching, dependency timeouts, fallback experiences, and application monitoring to reduce repeated database reads by ~39% and decrease timeout-related failures by ~24% during peak usage. Coordinated delivery activities across a 7-person engineering, product, analytics, and QA team, completing ~95% of committed feature work within planned release cycles.

Software Engineer at Accenture

January 1, 2014 - December 1, 2016

Modernized 12 legacy Java and Spring service components into standardized REST APIs, reducing integration development time by ~30% and eliminating duplicated business logic across three enterprise applications. Delivered back-end services for an enterprise workflow and case-management platform, shortening average request-processing cycles by ~26% and reducing manual status-tracking activity by ~41%. Decomposed tightly coupled application modules into reusable service-oriented components, enabling independent updates across 8 business functions and reducing cross-application release dependencies by ~23%. Automated build, integration-test, and deployment-preparation steps via Git-based CI/CD workflows, cutting manual release effort by ~49% and improving deployment consistency across three environments. Strengthened automated unit and integration testing to ~75% coverage, reducing post-release defects by ~28% and improving confidence during incremental client migrations. Facilitated tec

Junior Software Engineer at Accenture

July 1, 2012 - December 1, 2013

Constructed 6 Java and Spring back-end modules for an enterprise request-management application, completing ~94% of assigned sprint commitments within planned delivery windows. Resolved 40+ application and database defects by tracing failures across Java services, SQL queries, and integration points, reducing repeated issues by ~25%. Enhanced frequently used MySQL queries via indexing and query restructuring, improving response times by ~30% for selected application screens and reports. Authored 120+ unit and integration test cases for assigned back-end components, increasing test coverage from ~45% to ~70% and reducing regression defects during release testing. Communicated with a 6-person development team, business analysts, and QA engineers during sprint planning, stand-ups, and defect reviews, helping achieve ~90% first-cycle acceptance for assigned features.