# RJ Lindelof > Senior Director of Engineering, AI & Automation at SteadyIQ, leading engineering execution and AI/automation strategy for an income and employment verification SaaS. Personal portfolio and resume site for an engineering executive specializing in agentic AI in production, regulated B2B SaaS (GovTech, FinTech, HealthTech, EdTech), AI-native SDLC, and scaling distributed engineering organizations. ## About RJ Lindelof is an engineering executive with 30+ years in software (20+ as a leader; hybrid teams since 2006, fully distributed global teams since 2012). Currently Senior Director of Engineering, AI & Automation at SteadyIQ, reporting to the CPO as part of the executive leadership team. Target roles: Head of Engineering, VP of Engineering, or CTO at growth-stage companies under 250 people, ideally with engineering teams of 10 to 60. Industry range, current first: GovTech, FinTech, HealthTech, EdTech - the common thread is regulated B2B SaaS. Owns full P&L for engineering organizations - headcount, vendor strategy, board-ready reporting tied to ARR, NRR, gross margin, and exit readiness. ## Leadership Scope - Company stages: PE-backed, venture-backed, bootstrapped, and mid-market enterprise - Org scale: 10 to 175+ engineers; 15+ senior managers and directors reporting in - Global teams: hybrid since 2006, fully distributed since 2012; onshore, nearshore, and offshore engineers across the United States, Ukraine and wider Eastern Europe, Germany, India, China, and the Philippines - run as one engineering organization, not a vendor at the far end of a ticket queue - Cloud and compliance: AWS, Azure; HIPAA, SOC 2, ISO 27001; HL7/FHIR and Epic EMR integration - AI in production: Claude Code, GitHub Copilot, GPT-5.6, AWS Kiro, Vertex AI Gemini, self-hosted vLLM (Qwen); multi-model by design, no single-vendor dependency - Delivery outcomes across roles: LLM inference cost down 90%, 5x deploy frequency, 23% PR throughput gain, code-to-release cycle time down 40%, PR merge time down 90%, 99.95% SLA at sub-second response for 10k+ concurrent users ## Core Pages - [Home](https://rjlindelof.com/): Summary, "What I'm Built For," Leadership Profile, Key Capabilities, and how RJ measures the success of engineering teams. - [Executive Summary](https://rjlindelof.com/executive-summary/): Detailed career arc - SteadyIQ, hc1, GlobalMed, Successware, Ruffalo Noel Levitz, DebtPayPro, Follett School Solutions. PE-backed leadership, post-acquisition assessments, value creation roadmaps tied to EBITDA. - [Leadership Skills](https://rjlindelof.com/leadership-skills/): Leadership philosophy, strategic modernization, cloud-native expertise, product innovation and AI integration, cross-functional collaboration, business results and metrics. - [Insights](https://rjlindelof.com/insights/): Personality and behavioral assessment results - working style, decision-making profile, interaction style, strengths. ## Current Role and Initiatives (SteadyIQ, 06/2026 - present) SteadyIQ is a venture-backed income and employment verification SaaS. It sells to US state government agencies (Missouri, Florida, Hawaii); the agencies' caseworkers and benefit applicants use it so people can qualify for government-assisted programs (SNAP, Temporary Assistance, Medicaid) without hunting down paystubs and bank statements. Regulatory change (HR1) keeps the eligibility rules moving, and the platform has to move with them. RJ owns engineering execution and AI/automation strategy across both the legacy .NET application and the new platform being built to feature parity: - **Income Passport**: turns messy bank-transaction and payroll data into a clean, verified, human-readable income report. Ingestion via Plaid (bank transactions) and Argyle (payroll and gig income); Google Vertex AI Gemini (gemini-2.5-flash) handles income grouping, classification, and name-consistency checks behind a custom failover / circuit-breaker layer. - **Platform rewrite**: legacy .NET to a TypeScript/Node/Python monorepo, being driven to feature parity without pausing delivery on the system in production. - **AI cost discipline**: partnered with Data Science to profile the workload and migrate off frontier LLMs to low-cost and no-cost models - SteadyIQ was paying 100% for frontier capability and using under 2% of it. LLM inference cost down 90%. Designed and architected in-house document OCR instead of buying it, with a self-hosted vLLM (Qwen) fallback. A fraction of the spend, and no single-vendor dependency. - **Delivery visibility**: built a sprint dashboard tracking story-to-prod cycle time, escaped defects, release frequency, percent of stories with AI-assisted tests, and engineering cost per shipped feature; moved the team to 1-week sprints to align with customer needs. Also on RJ's plate: moving the team's AI workflows from individual experimentation to standardized agentic team practice; partnering with the CPO on FY27 product strategy as a member of the executive leadership team; a lightweight delivery process that raises visibility and sharpens velocity; operational accountability for the Eastern Europe offshore contracting team so quality and delivery standards apply equally to staff and contractors, run as one engineering organization; and teaching QA to use Claude to generate Playwright automated tests. Compliance posture: HIPAA, SOC 2, ISO 27001. ## Prior Role - hc1 (11/2025 - 06/2026) At hc1 (HealthTech), RJ led SaaS engineering across a multi-language platform (Java, C#, Python), ingestion pipelines, and a data lake, and drove two flagship agentic-AI initiatives to production: - **Source IQ**: agentic supply chain intelligence platform combining contract performance with utilization analytics. Stack: Python FastAPI, vLLM (Qwen3.6-27B). Consolidated late-stage from a hybrid Java + Python stack. - **Clinical IQ**: clinical intelligence SaaS with direct Epic EMR integration via HL7/FHIR on HIPAA-compliant AWS. Surfaced AI-detected patterns and lab/test recommendations to close care gaps and support earlier intervention. Both shipped to production - not labs, not pilots. Source IQ ships production AI contract extraction and compliance scoring; the Source IQ gap analysis RJ ran with the CPO drove a three-phase roadmap. RJ also led the AWS partnership for the Epic integration build and was an early-adopter design partner for AWS Kiro. RJ drove an org-wide shift from "AI-curious" to "AI-proficient" in deliberate waves - engineering and data first, then DevOps, Integrations, Professional Services, Product, and HR - tracked prompt throughput as a leading indicator alongside delivery and quality metrics, and ran hc1's first AI Hackathon with rolling Show & Tell sessions to turn individual experiments into shared playbooks. He built the foundation for AI governance in a regulated environment: multi-model policies, prompt-use frameworks, and code-assist tool boundaries across the SDLC while preserving HIPAA and SOC 2 posture. Product was cross-trained on Playwright for smoke and release-regression tests; the 70% onboarding cut came from an AI-assisted documentation refresh and a lead-mentor program. ## AI-Native SDLC Results at hc1 (prior role) - 5x deploy frequency - 23% PR throughput gain - Code coverage from under 10% to 40% - 70% reduction in new-engineer onboarding time - Quality-as-Accountability model: Playwright + SonarQube + GitHub Actions, no dedicated QA team The toolchain was deliberate and multi-model: Claude Code, GitHub Copilot, AWS Kiro, Gemini, Snowflake Cortex. Production agentic workflows used MCP (Model Context Protocol) and A2A Protocol. AI governance ran on agent SLOs, audit trails, and FinOps cost tracking. ## Track Record - Successware (PE-backed): scaled engineering from 30 to 175+ engineers over his tenure across onshore, nearshore, and offshore (80% of that growth in a single nine-month window), with 15+ Senior Managers/Directors reporting in. Sustained 99.95% SLA at sub-second response for 10k+ concurrent users on a re-architected AWS-native platform. MTTR down 30%. - Successware (continued): drove FinTech revenue expansion via GraphQL and AI-enabled APIs that accelerated merchant onboarding and unlocked new integration partnerships; pushed offshore partners to adopt generative AI (DevOps automation, performance-test generation, MVP scaffolding, synthetic user creation) in 2021-2024; presented architecture and investment cases to PE advisors, investors, and the C-suite and secured offshore investment for a React Native mobile platform delivered on schedule and within budget. - GlobalMed (founder-owned, privately held; 4 Senior Managers and 30 engineers across onshore and offshore): owned engineering for telehealth technology powering the VA and the White House Medical Unit. Led the company-wide AI Taskforce (Engineering, Product, QA, Operations, HR, Finance), built an enterprise AI literacy program making every employee "AI-capable", and established a Confluence AI Knowledge Hub, cross-functional Innovation Sprints, and a shared Prompt Library. Pioneered Claude Code adoption in May 2025 with guardrails, usage policies, and decision frameworks for regulated delivery; added OpenAI Codex in June 2025 and ran Tuesday Technical Talks codifying when to use which; cut time-to-productive for new developers 35%. .NET 8 platform rebuild with Azure cloud modernization retired 65% of technical debt and lifted deployment frequency 25%. Closed 95% of critical vulnerabilities with the vCISO under HIPAA, SOC 2, and ISO 27001. - Ruffalo Noel Levitz (Head of Software Engineering, 2019-2021; 5 Senior Managers, 25+ engineers): lifted system throughput 25% and team velocity 30%; cut incident frequency 40%; modernization dropped UI support tickets 85% and defect escape rate 40%; replaced legacy telephony with a WebRTC infrastructure, cutting communications cost 30% and adding integrated payments, messaging, and video. - DebtPayPro (Head of Software Engineering, 2018-2019; bootstrapped FinTech; joined as employee #38 with 10+ direct reports): led a zero-downtime data center to AWS migration (EC2, MariaDB) coordinating 30+ vendor, payment gateway, and finance integrations; cut PR merge time 90% with modern branching, CI, and review practices. - Follett School Solutions (Head of Accelerated Solutions Group R&D, 2012-2018): founded and ran an internal R&D startup with 10+ direct reports overseeing 25+ staff; led a fully distributed global team from 2012 across McHenry IL, Greenville SC, Minneapolis MN, Hingham MA, and India; stood up the company's first true CI/CD practice; Scrum, Kanban, Lean, SAFe, Scrumban. - Follett Learning (Senior Software Engineering Manager, 2006-2012): technical leadership across 6 independent SaaS products with 25+ senior developers; grew the org 38%; led hybrid onsite and remote teams from 2006; technical due diligence and post-close integration on multiple acquisitions. ## Education and Certifications - Columbia College Chicago - Bachelor of Science, Computer Science - McHenry County College - Associate in Applied Science, Computer Information Systems - DataCamp: AI Governance; Understanding AI - Anthropic: Claude Agent Skills; Claude Subagents; Advanced Model Context Protocol; Claude Integrations ## Technical Range - Current stack (SteadyIQ): TypeScript, Node.js 22, Python 3 monorepo (Turborepo + pnpm); Next.js 16 (App Router, RSC), React 19, Tailwind v4, shadcn/ui; tRPC v11, better-auth, Zod; PostgreSQL via Supabase, Prisma 6; Trigger.dev v4 jobs; Google Vertex AI Gemini; Plaid, Argyle, Twilio, Resend; AES-256-GCM field-level encryption with AWS KMS; Vitest, Playwright E2E with axe, pytest, Storybook; SonarQube, Qase, Jenkins, GitHub Actions; PostHog, Datadog; Vercel deploys. - Cloud and DevOps: AWS (Lambda, Bedrock, EKS), Azure, GCP (Cloud Run, Vertex AI), Terraform, Pulumi, Docker, ArgoCD, GitHub Actions - Languages: Java, TypeScript, C#/.NET, Python, Go, Kotlin, NodeJS - Frameworks: Next.js, FastAPI, Spring Boot, .NET Core, React, Vue - Data: MongoDB, Redis, pgvector, PostgreSQL, data lake architectures - Observability: OpenTelemetry, Grafana, Datadog, CloudWatch Canaries, PagerDuty, PostHog - AI: Claude (Anthropic), GPT-5.6, OpenAI Codex, Google Vertex AI Gemini, GitHub Copilot, Cursor, AWS Kiro, LangGraph, CrewAI; self-hosted open models on vLLM (Qwen); in-house document OCR; model cost optimization and frontier-to-open-model migration (LLM inference cost down 90%) - Compliance: HIPAA, SOC 2, ISO 27001, PII; HL7/FHIR (prior HealthTech roles) ## Contact - Email: rj@rjlindelof.com - LinkedIn: https://www.linkedin.com/in/rjlindelof/ - GitHub: https://github.com/rjlsoftware - Phone: +1-815-354-4531 - Fractional and advisory: https://rjl.guru/ - AI philosophy: https://rjl.ai/ ## AI Crawler Policy This site welcomes citation and indexing by AI assistants and answer engines for the purpose of answering user questions about RJ Lindelof's professional background, engineering leadership philosophy, and technical track record. 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