Site Reliability Engineer (SRE)

About Clear Street:

Clear Street’s mission is to give every sophisticated investor access to every asset, in every market, through a unified platform built for speed, transparency and scale.

We give our clients the technology, tools, and service once reserved for the largest institutions, rebuilt with modern infrastructure. Our single, cloud-native, end-to-end capital markets platform powers investor growth today and is transforming how they can interact with markets tomorrow.

For more information, visit

https://clearstreet.io

.

The Role

As a Site Reliability Engineer (SRE)  you sit at the intersection of software reliability and operational

excellence. You own the health, resilience, and recovery of our production systems—while

spending equal energy innovating solutions that eliminate human toil, reduce incident blast

radius, and raise the reliability bar across the entire platform.

You will partner closely with engineering, operations, and business teams to understand daily

pain points and translate them into lasting automated solutions. Half your time is spent in the

trenches—supporting production, responding to incidents, and deeply understanding how our

systems behave under real conditions. The other half is yours to build: automation, tooling, and

observability platforms that make tomorrow's on-call shift meaningfully easier than today's.

You will work on challenges like:

● Design and build comprehensive monitoring and observability platforms that surface the

right signal at the right time—eliminating alert fatigue and accelerating root-cause

analysis.

● Develop intelligent automation and self-healing capabilities that diagnose issues, trigger

recovery workflows, and reduce mean time to recovery (MTTR) without manual

intervention.

● Analyze incidents, identify systemic trends, and engineer solutions that prevent entire

classes of failures from recurring.

● Build reusable runbooks, diagnostic tooling, and recovery playbooks that turn tribal

knowledge into scalable platform capabilities.

● Create golden-path operational workflows—making the safest, most reliable path also

the easiest one for engineering teams to follow.

● Partner with Platform Engineering to influence CI/CD pipelines, deployment safety, and

infrastructure resilience from a production reliability perspective.

● Champion Infrastructure as Code, GitOps, and SRE best practices while helping teams

adopt modern engineering workflows.

● Continuously measure production health through SLIs/SLOs/SLAs, and drive

engineering priorities based on reliability data.

● Explore emerging technologies—including AI-assisted diagnostics and developer

tooling—that transform how we operate production systems.

The Team

We believe resilient systems are built by engineers who understand them end to end.

Our Production Engineering team is the first and last line of defense for our production platform.

We treat reliability as a product, with uptime and engineer experience as our north stars. We

combine the discipline of SRE with a builder's mindset: when we see a recurring problem, we

build a solution—not a workaround.

You will work across every engineering and operations team to understand failure modes, quantify

reliability gaps, and build platform capabilities that scale with the organization. Whether it's

reducing MTTR from hours to minutes, building self-service diagnostic tools, or designing

proactive alerting that catches issues before customers notice, your work will have immediate,

measurable impact.

If you're passionate about making production systems invisible to end users—and you get

energy from both firefighting and building the systems that make fires less likely—you'll thrive

here.

What We're Looking For

We're looking for engineers who combine operational instinct with a builder's discipline.

You should have:

● Strong hands-on Python skills—this is your primary language for automation and tooling.

● Experience in SRE, Production Engineering, Platform Engineering, or a related discipline

with direct production ownership.

● Proven track record of building automation and diagnostic tooling that improved recovery

times or reduced operational toil.

● Deep familiarity with cloud-native technologies—Kubernetes, containers, distributed

systems—and how they fail in production.

● Experience with observability platforms such as Datadog, and a strong intuition for what "

good" monitoring looks like.

● Exposure to Infrastructure as Code (Terraform) and GitOps-based deployment

workflows (ArgoCD, GitHub Actions, or similar).

● Familiarity with the broader technology stack: Java, Go, Kafka, Redis, Snowflake, and

Postgres.

● Strong analytical and problem-solving skills—you thrive on ambiguous, high-stakes

production problems.

● A product mindset applied to operational tooling: you think about usability, adoption, and

documentation when building internal solutions.

● Excellent communication skills and the ability to work fluidly across engineering,

operations, and business stakeholders.

● Self-starter mentality—you identify opportunities, take initiative, and deliver with minimal

supervision.

● Curiosity and a continuous learning mindset; fintech or financial industry background is a

plus.

The Technology You'll Work With

You'll operate and build on a modern cloud-native platform that includes:

● Kubernetes & AWS

● Terraform & ArgoCD

● GitHub Actions

● Kafka, Redis

● PostgreSQL & Snowflake

● Datadog

● Python, Go, Java

● gRPC & Protobuf

● Internal Platform APIs and Developer Tooling

What Success Looks Like

Within your first year, you'll have made a measurable impact on production reliability. Success l

ooks like:

● Reducing mean time to detection (MTTD) and mean time to recovery (MTTR) across key

production systems.

● Building automation that handles a meaningful percentage of incident scenarios without

human intervention.

● Becoming a trusted subject matter expert for core platform components and their failure

modes.

● Delivering observability and diagnostic tools that other engineers actually use and

depend on.

● Establishing SLO baselines and driving engineering investment based on reliability data.

● Spending less of your time—and your teammates time—on repetitive manual toil.

Your impact won't be measured by the number of incidents you respond to—it will be measured

by how reliably our systems run and how quickly we recover when they don't.

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