Executive Summary
RJ Lindelof is Senior Director of Engineering, AI & Automation at SteadyIQ, where he owns engineering execution and AI/automation strategy and reports to the CPO as part of the executive leadership team. SteadyIQ is an income and employment verification SaaS: its Income Passport product turns messy bank-transaction and payroll data into a clean, verified, human-readable income report. The model is B2B2C - SteadyIQ sells to US state government agencies (Missouri, Florida, Hawaii), and those agencies' caseworkers and benefit applicants use it, so people qualify for SNAP, Temporary Assistance, and Medicaid without hunting down paystubs and bank statements. He leads the platform rewrite from a legacy .NET application to a TypeScript/Node/Python monorepo, which he is driving to feature parity, with Google Vertex AI Gemini behind a custom failover and circuit-breaker layer for income grouping, classification, and name-consistency checks, and Plaid and Argyle supplying bank-transaction and payroll/gig income data. With the Data Science team, he took the platform off frontier LLMs and onto low-cost and no-cost models once measurement showed the workload was drawing under 2% of the frontier capability it was paying 100% for, and he designed and architected document OCR in house, with a self-hosted vLLM (Qwen) fallback, instead of buying it. Regulatory change keeps the eligibility rules moving, so the platform has to move with them - all under HIPAA, SOC 2, and ISO 27001.
At hc1, he was Senior Director of Software Engineering and led the full SaaS engineering org through an AI-native transformation across a multi-language platform (Java, C#, Python), ingestion pipelines, data lake, post-merger integration, and two flagship initiatives anchored in agentic AI. Source IQ was a greenfield agentic supply chain intelligence platform combining contract performance with utilization analytics on Python FastAPI and vLLM (Qwen3.6-27B), consolidated late-stage from a hybrid Java + Python stack. Clinical IQ was a clinical intelligence SaaS with direct Epic EMR integration via HL7/FHIR on HIPAA-compliant AWS, surfacing AI-detected patterns and lab/test recommendations to close care gaps and support earlier intervention.
Over 20 years of engineering leadership across GovTech, FinTech, HealthTech, EdTech, and regulated B2B SaaS. At Successware (PE-backed), he scaled the engineering org from 30 to 175+ engineers in nine months across onshore, nearshore, and offshore - delivering 99.95% SLA at sub-second response for 10k concurrent users on a re-architected AWS-native platform. At GlobalMed, he owned engineering for telehealth technology powering the VA and White House Medical Unit, drove a .NET 8 platform rebuild that retired 65% of technical debt, and partnered with the vCISO to close 95% of critical vulnerabilities under HIPAA, SOC 2, and ISO 27001 posture.
His leadership in PE-backed environments includes 30-60 day post-acquisition technology assessments, value creation roadmaps tied to EBITDA impact, and board-ready reporting that connects engineering investment to business outcomes. He has presented architecture and investment cases directly to PE advisors and the C-suite, has owned full P&L for engineering organizations including budget and compensation, and has driven post-merger integration including portfolio rationalization and organizational alignment to right-size combined orgs.
RJ architects for longevity, not flash. He embeds CI/CD pipelines, enforces quality gates with SonarQube and GitHub Actions, and drives velocity with clear standards and metrics. At hc1, he built a "Quality as Accountability" model with three-step testing (Smoke, Targeted, Full Regression) using Playwright and GitHub Actions quality gates - no dedicated QA team required. Engineering, Product, and Services shared release accountability; AI-assisted test generation lifted code coverage from under 10% to 40%. See how he measures engineering success.
AI is not layered on. It is built in. At hc1, GitHub Actions, Claude Code, Copilot, and AWS Kiro drove code generation, test synthesis, cloud architecture scaffolding, and documentation as first-class CI/CD pipeline stages. The toolchain was multi-model by design - Kiro, Claude, Copilot, Gemini, Snowflake Cortex - with no single-vendor dependency. The results: 5x deploy frequency, 23% PR throughput gain, and a 70% reduction in new-engineer onboarding time. Production agentic workflows used MCP and A2A protocols; AI governance ran on agent SLOs and audit trails. He carries the same multi-model, no-single-vendor discipline into SteadyIQ's AI-native SDLC. Learn more about his AI integration approach.
He leads with clarity, challenges assumptions, and builds high-performing, globally distributed teams that own their outcomes. His engineering cultures run on trust, autonomy, and accountability - because those are the conditions where high-impact work gets done. Personal standards set the bar - uncompromising attention to detail at the architecture level, the PR level, and the post-mortem level. Explore his detailed leadership philosophy.
RJ is also available for fractional CTO and interim technology leadership engagements. Whether you need a full-time leader or a strategic advisor, he delivers. Every time.