Senior Director · Software Engineering · Applied AI

Software organizations,
engineered to deliver.

I build engineering organizations that ship with speed, quality, and intent. Chris Rivera — 15 years turning ambiguous problems into scalable platforms, high-performing teams, and measurable outcomes.

Work with me Download résumé

Available for advisory & leadership roles

Chris Rivera · San Jose, CA

Building software teams
that actually ship.

I spent the first decade of my career as an individual contributor — deep in systems design, data pipelines, and distributed architecture. I know what good engineering looks like from the inside.

The second half of my career has been about multiplying that impact. I've built engineering organizations from scratch, modernized legacy platforms, and shipped products that changed how industries operate. That combination — technical depth plus organizational leadership — is what makes the difference between teams that talk about delivering and teams that do.

"The best engineering organizations aren't just technically excellent — they're aligned, intentional, and relentless about outcomes."

// Leadership wins

Outcomes, not activity.

0×

Team growth

Scaled engineering org from 4 to 15+ engineers across platform, data, and product

Revenue growth

Delivered in ARR growth in 24 months

Years of experience

Building and shipping software across rail, logistics, and automotive industries

→ AI-driven engineering

Led enterprise AI adoption across 4 product lines — LLM-assisted triage, code review, and incident summarization — cutting mean-time-to-resolve by 40%.

→ Platform modernization

Architected migration from aging monolith to event-driven microservices on GCP. Zero customer-facing downtime across a 14-month transition.

→ Engineering culture

Built on-call culture, incident process, and career ladder from scratch. Voluntary attrition dropped to under 5% two years running.

// Applied AI

AI that moves the business —
in domains that can't be wrong.

0 AI products shipped

0% Reduction in triage time

0 Model providers integrated

100% Calls traced in production

Architecture stack

Product Interface Chat / API / Embedded widgets

↓

Orchestration LangChain · custom agent loops

↓

Model Routing Tiered by cost, latency & task type

↓

Context Layer RAG · vector store · memory

↓

Tool Use Internal APIs · structured outputs

↓

Observability Tracing · evals · cost tracking

Tiered model routing

Tier 1 — FastGPT-4o-mini · Haiku

Tier 2 — BalancedGPT-4o · Sonnet

Tier 3 — Powerfulo1 · Opus

MLOps governance

Prompt versioning

Eval framework

Cost attribution

Responsible AI policy

Retrieval Enterprise

RAG Pipelines

Production retrieval-augmented generation over proprietary data. Semantic search, re-ranking, and citation-grounded outputs.

< 800ms p95 retrieval latency

Agents Workflow

Autonomous Agents

Multi-step agent workflows with tool use, structured output, and human-in-the-loop checkpoints for high-stakes decisions.

4 products shipped with agent patterns

Governance MLOps

AI Governance

Prompt versioning, model evaluation frameworks, cost allocation, and responsible AI policies across the org.

100% model calls traced & evaluated

// Solo build

PostMine —
insights mined automatically.

A SaaS product I designed, built, and shipped solo. PostMine extracts structured insights from unstructured content — articles, transcripts, reports — using a retrieval-augmented pipeline I built from scratch.

01Connect any content source
02Automatic insight extraction via LLM pipeline
03Search, filter, and export structured results

Visit PostMine →

Pipeline

01 Ingest content RSS · API · Upload

02 Chunk & embed OpenAI Embeddings

03 Store vectors pgvector · Supabase

04 Retrieve context Semantic search

05 Generate insights GPT-4o · structured output

06 Deliver to user REST API · Webhooks

AstroReactOpenAISupabasepgvectorStripeVercelTypeScript

// Featured projects

Selected work.

01 PLATFORM ENGINEERING

Rail Operations Intelligence Platform

End-to-end data pipeline and ops dashboard for the railroad industry, processing hundreds of thousands of crew movements.

PythonKafkaPostgreSQLReactGCP

02 APPLIED AI

AI-Powered Inspection Workflow

Computer vision pipeline for automated vehicle inspection at auction lanes. Reduced inspection time by 60% and standardized condition grading across 10+ sites.

PyTorchFastAPICloud VisionReact Native

03 DEVELOPER PLATFORM

Internal Developer Platform

Self-service infrastructure platform enabling teams to provision, deploy, and monitor services without ops tickets. Reduced deployment lead time from days to minutes.

TerraformKubernetesGitHub ActionsGo

04 MARKETPLACE

Digital Auction Platform

Real-time vehicle auction system handling concurrent bidding across thousands of simultaneous participants. Built for zero-downtime during peak auction events.

Node.jsWebSocketsRedisPostgreSQL

05 DATA ENGINEERING

Logistics Data Mesh

Domain-oriented data architecture connecting rail, trucking, and port operations data. Serves analytics, reporting, and ML feature stores across 5 business units.

dbtBigQueryAirflowLooker

06 PRODUCT

PostMine

Solo-built SaaS product for mining structured insights from unstructured content. Full-stack from infrastructure to product design.

AstroOpenAIStripeSupabaseVercel

Delivered for operators who can't afford downtime.

Rail · Transit · Logistics

Automotive Marketplaces & Auctions

// Résumé

Experience.

PS Technology

2023 — Present

Remote / San Jose, CA

Rail · Transit · Logistics

Director of Engineering

Led multiple cross-functional engineering pods across five product lines, coordinating onshore/offshore teams, QA, product, and customer stakeholders to deliver mission-critical rail software.
Defined AI architecture for regulated enterprise workflows, including a governed intelligence layer spanning LLM access, RAG-based retrieval, tool execution, safety, and auditability.
Architected conversational AI and agentic workflows over complex operational systems, with policy-engine guardrails, human escalation flows, and deterministic handling of compliance-critical decisions.
Drove engineering productivity by championing AI coding tools and agentic automation across pods, measurably accelerating team throughput and decision quality.
Built high-performing, inclusive engineering teams through clear expectations, consistent feedback, and a culture of psychological safety and ownership.
Owned full-stack platform modernization and delivery governance across multi-million-dollar customer programs, contributing to a 2× increase in recurring subscription revenue.

Integrated Auction Solutions

2016 — 2022

Austin, TX

Automotive Marketplaces

Director of Product & Engineering

Built real-time auction bidding engine supporting 1,000+ concurrent users per event
Led integration with Cox Automotive and ADESA platforms, expanding market reach 4×
Managed a team of 5 engineers across frontend, backend, and QA functions
Reduced critical bug escape rate by 70% through test automation and code review standards

Earlier Career

2008 — 2013

Various

Software Engineering

Software Engineer → Senior Engineer

Progressed through IC roles at logistics and SaaS companies, specializing in backend systems and data pipelines
Built foundational expertise in distributed systems, SQL query optimization, and REST API design

Education

Master of Science in Information Technology

Purdue Global · West Lafayette, IN

Bachelor of Science in Cloud Computing and Solutions

Purdue Global · West Lafayette, IN

Certifications

Google Cloud Professional Cloud Architect

Google Cloud Professional Data Engineer

Project Management Professional (PMP)

Technology

PythonTypeScriptGoSQLReactAstroNode.jsPostgreSQLBigQueryRedisKubernetesTerraformGCPKafkaAirflowdbtOpenAI APILangChain

Ready to build something
and actually ship it?

Let's talk → LinkedIn ↗ Download résumé

Software organizations, engineered to deliver.

Building software teams that actually ship.