Senior Staff Engineer

Sprinto is an Autonomous Trust Platform that centralizes trust requirements across security frameworks, vendors, and customers.

Sprinto autonomously executes tasks needed to maintain trust across compliance, audits, risk management, vendor risk, privacy, and AI governance, enabling organizations to maintain a strong, reliable trust posture without draining operational bandwidth and resources on repetitive tasks.

Backed by top-tier investors such as Accel, Elevation, and Blume Ventures, we’ve raised $31.8M in funding to fuel our mission. Trusted by over 4,000 organizations across 75 countries, Sprinto helps organizations stay audit-ready, manage real-time risks, and scale fearlessly. With 300+ native integrations and AI-driven automation, Sprinto supports 200+ global security standards natively, including SOC 2, ISO 27001, GDPR, HIPAA, PCI-DSS, and more. Sprinto's extensible architecture enables organizations to build and support an infinite number of custom integrations and frameworks.

Founded in 2020 by second-time founders Girish Redekar and Raghuveer Kancherla, Sprinto powers compliance for organizations like Whatfix, Encora, Anaconda, Whatnot, Ultrahuman, WeWork, Everstage, AI Foundation, HackerRank, and many more.

Life as a Sprinter -

Nobody succeeds at Sprinto by staying in their lane.

We are organized around problems, not job titles. Sprinters take ownership beyond their role, solve hard problems, and care deeply about the impact they create. If something can be improved, fixed, or built, we don't wait for permission; we step in.

Being remote means we rely less on proximity and more on trust. We write things down, communicate openly, and move quickly because great teams aren't built by sitting together; they're built by pulling in the same direction.

We believe progress beats perfection, feedback is a gift, and doing the right thing matters, even when nobody is watching.

And while we move with urgency, we never move alone.

The mission -

Autonomy is the easy half. Making it defensible is the hard half.

What the platform produces is not a suggestion that a customer can take or leave. It's used as fact by auditors and enterprise buyers whose decisions depend on us being right. Wrong in one direction, a customer loses a certification because of us. Wrong in the other, we bury them in noise until they stop reading anything we send.

Your mission is to make a defensible half, making agent judgment something a third party will accept.

Agents whose output nobody re-checks. You'll see how we prove an agent is trustworthy: evaluation harnesses that gate releases rather than run quarterly, golden sets built with real compliance experts, regression suites assembled from production traces, and drift detection that fires before a customer notices. Not a set of scripts — a platform every other team builds on. You'll know it works when a compliance lead stops reviewing a category of output, and nothing breaks.

A system that can prove what it said, and admit when it didn't know. Compliance is a claim about the past, which means state as of a date has to be held separately from when we learned it, and every artefact has to carry unbroken provenance from the source system to the audit package. The other half of the problem is honesty under failure. At several hundred connectors, partial failures are normal, and a connector returning nothing because Okta is down must never look like a control genuinely failing. Passing, failing and unknown are three different states, and that distinction has to survive all the way to the interface.

Beyond those two, there are surfaces you'll work across without owning alone: tenant isolation and enterprise identity as we move upmarket, the inference economics that decide whether continuous monitoring is viable at scale, and how we model 200 frameworks so the next one is cheap. And since every engineer here will be building with agents within a year, we'll expect the practice to be better across the org because you joined.

Someone who has built something that changed the shape of the work. Not a prototype — a system where an LLM took autonomous, multi-step action against real data and real users, and displaced something people used to do by hand. We'll want to hear what it replaced, what it cost, what its failure rate was, and how you measured it.

An engineer who treats the model as an untrusted subsystem. Constrained outputs, independent verification, thresholds that escalate rather than guess, a clear line between what the model decides and what it only proposes. We're more interested in how your system detected and contained a bad output than in how it tried to prevent one.

Depth in at least two of these, with room to pick up the rest here: production LLM and agent systems; temporal and provenance data modeling; high-fan-out integration reliability; multi-tenant and enterprise identity; inference cost engineering; domain modeling for messy regulatory rules.

10+ years building software, at least two of them at Staff scope — setting technical direction that engineers outside your reporting line followed.

Range. Some quarters this role is an architect setting direction, some quarters it's the person taking on the problem nobody has cracked, some quarters it's carrying a team through a hard delivery. The people who do well here read what the company needs and adapt.

Willingness to challenge how we build, and to hold the line when it counts. We're hiring partly for disagreement — on our architecture, our agent design, our standards. That includes telling go-to-market what we can't yet defend, and offering a path rather than a refusal.

Influence without authority. Nobody on this team reports to you. Your leverage is clarity, credibility and the quality of your reasoning across Engineering, Product, Security and CX — and since we're remote-first, most of that happens in writing.