Tim Williams
Senior Backend and AI Engineer
About
Backend Software and AI engineer building reliable Backend Services, Data and AI pipelines at SaaS scale. I design clear APIs, production-grade ETL/ELT, and Kubernetes-first microservices with strong CI/CD, observability, and testing. Programming Language agnostic, performance-minded, and delivery-oriented.
Experience
Software Engineer / AI Engineer · Canopy
Remote
2024 — Present
- Own backend architecture for Communication (Email, Notifications, In-App Messaging, Comments, etc..) features; designed clear service boundaries and APIs used by web and internal tools.
- Manange, build and maintain Python, Java and Kotlin microservices, and ML Models and Pipelines on Kubernetes in a high traffic, multi-tenant SaaS environment
- Partnered with Product on requirements and delivery; mentored engineers on testing patterns, code reviews, and on-call hygiene.
Lead Software Engineer (Full Stack Application Development, Data Engineering, AI) · Marketstar
Remote
2021 — 2024
- Integrated LLM-powered summarization and insights into internal management apps; shipped reliable prompt/response pipelines with auditability.
- Built Sales intelligence Models and Pipelines, Forcasting, Data Analysis.
- Prototyped multi-modal and fine-tuning workflows; built and maintained GPU-backed training/test queues on Kubernetes.
Data Engineer · Marketstar
Salt Lake City, UT
2020 — 2022
- Implemented robust ingestion patterns (CDC/incremental) with Data Factory and orchestrated transforms into a governed warehouse.
- Optimized heavy queries and indexing strategies in SQL Server/Synapse; significantly reduced runtime and compute cost.
- Authored internal SDK/utilities to standardize pipeline scaffolding, configuration, and error handling.
Projects
Direct-to-Provider Email/Calendar/Contacts SDK
Rebuilt a Nylas-style SDK for Google, Microsoft, iCloud, and IMAP using RxJava 1.3 + Vert.x; microservice-ready with backoff, retries, and typed models.
Questionnaire to CRM Sync (Tax SaaS)
Diffs client-submitted questionnaire data against CRM records (e.g., address/phone), proposes updates, and lets staff approve one-click merges.
AI Questionnaire & Document Checklist creation for Tax Practitioner Smart Intake (Tax SaaS)
GPU Training Cluster
Kubernetes GPU nodes for fine-tuning domain models; queue-based job runner with metrics/traces, artifact versioning, and reproducible seeds.
.sav Structure Discovery Pod
K8s pod that inspects SPSS .sav files to infer schema/structure for downstream pipelines; exposes results via API and dashboard.