About
About RJ Lindelof
Player-coach engineering executive. 20+ years leading teams in regulated GovTech, HealthTech, EdTech and FinTech SaaS - and I still write code.
My Background
I'm Senior Director of Engineering, AI & Automation at SteadyIQ, a fully remote GovTech company whose platform helps government agencies verify income for benefits programs. I own engineering execution and AI/automation strategy, partner with the CPO on product strategy, and lead the rewrite of the legacy platform onto a modern TypeScript/Node/Python stack. Before SteadyIQ I led SaaS engineering at hc1 (healthcare analytics), GlobalMed (telehealth for the VA and White House Medical Unit), and Successware (PE-backed B2B SaaS).
Across PE- and venture-backed companies and mid-market enterprises, the mandate has been the same three things - technology strategy, platform scalability, and AI adoption - always in close partnership with product. In practice that has meant scaling multi-tenant SaaS platforms, putting agentic AI systems into production rather than leaving them in pilots, and modernizing cloud infrastructure across AWS and Azure, with automation, performance, and reliability built into high-growth environments as a matter of course. I hold engineering execution to the business strategy it serves: faster delivery, lower infrastructure cost, and results that customers and investors can both measure.
I lead with autonomy and accountability - set clear objectives, then get out of the way - hire for curiosity over credentials, and treat infrastructure and reliability as strategic peers, not a service desk. I have no patience for AI theater: I measure shipping velocity, reliability, and customer outcomes, not the appearance of work. In healthcare I've shipped Epic EMR integrations over HL7/FHIR and held HIPAA, SOC 2, and ISO 27001 posture in production. I've led hybrid teams since 2006 and fully remote teams since 2012 - global orgs spanning onshore, nearshore, offshore, and Eastern European engineering - so distributed engineering is my default operating model, not an accommodation.
I'm all in on what we're building at SteadyIQ and I'm not job hunting - but I've kept the door open in every role I've ever held, and this one is no different. If you're the right company with the right fit, I'm always glad to have the conversation - let's talk. I still write and speak on operationalizing AI across the engineering org, and I enjoy comparing notes with other leaders working the same problems - AI-native SDLC, agentic delivery, and platform modernization in regulated B2B SaaS. I'm in the Greater Chicago area, fully remote since 2015. The contact page is the fastest way to reach me.
Press Kit
For event organizers, editors and podcast hosts. Use any of this as written.
Short bio
RJ Lindelof is Senior Director of Engineering, AI & Automation at SteadyIQ, where he leads engineering for a GovTech income and employment verification platform. A player-coach engineering executive with 20+ years in regulated B2B SaaS, he writes about putting AI to work across the software delivery lifecycle at RJL.ai.
Longer bio
RJ Lindelof is Senior Director of Engineering, AI & Automation at SteadyIQ, a fully remote GovTech company whose platform helps government agencies verify income for benefits programs. Before SteadyIQ he led SaaS engineering at hc1 (healthcare analytics), GlobalMed (telehealth for the VA and White House Medical Unit) and Successware (PE-backed B2B SaaS), where he scaled engineering from 30 to 175+ at 99.95% SLA. Earlier, he founded and ran Follett's internal K-12 R&D group and led engineering at the FinTech startup DebtPayPro. He has led distributed teams since 2012, still writes code, and writes the Field Notes on RJL.ai about what changes when AI writes most of the code. He is based in the Greater Chicago area.
Headshot
Download the headshot (PNG, 1024 x 1024).
Topics I speak and write on
- Where the bottleneck moves when AI writes most of the code - review, QA and requirements.
- An operating model for AI in the SDLC, not a tooling purchase.
- Who signs for agent-written code: accountability, identity and governance for agents.
- The AI Platform Map: the nine layers that make it cheap to trust AI-generated software.
- AI adoption as a trust problem, and the J-curve finance needs to hear about before the budget is spent.
Booking and interview requests: the contact page, topic "Speaking or writing".
Where to Next
Read what I have learned putting AI into production, or skip straight to a conversation.