Site Reliability Engineer

Aisle

New York (NY)

On-site

USD 140,000 - 190,000

Full time

15 hours ago

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Job summary

Aisle is building real-time retail tech that nudges actions and optimizes outcomes as they happen. We’re seeking a Senior SRE/DevOps engineer to own reliability, scalability, and observability of our GCP-based infrastructure in the US market.

You will design and implement monitoring with Datadog, manage IAM and security, participate in on-call rotations, incident response, and post-mortems, and drive durable improvements across distributed systems and production workflows.

Qualifications

4+ years in SRE, DevOps, or infrastructure roles.
Strong hands-on experience with GCP.
Experience with event-driven/serverless architectures (Pub/Sub, Cloud Functions).
Familiarity with IAM, security best practices, and observability (Datadog).

Responsibilities

Own reliability, scalability, and observability of our GCP-based infra.
Design monitoring and alerting with Datadog; create monitors-as-code.
Manage IAM, service accounts, and security practices across cloud.
Participate in on-call rotations and post-mortems; drive systemic improvements.
Stabilize core infrastructure under heavy concurrent load.

Skills

SRE/DevOps

GCP

Event-driven systems

Observability (Datadog)

Security & IAM

Node.js

Backend engineering

AI in engineering

On-call & incident response

Tools

Cloud Functions

Pub/Sub

Workflows

Kubernetes

Vercel

PostgreSQL

Prisma

Redis

BullMQ

OpenClaw

LLM gateway

pgbouncer

Node.js

TypeScript

Job description

Physical retail has always been a black box - brands ship product, run static promotions, and wait weeks (or months) to understand what actually happened.

Aisle builds a real-time control layer on top of physical retail. We connect shopper actions, incentives, and outcomes into a continuous feedback loop, so brands can trigger, measure, and optimize retail performance while it’s happening - not after the fact.

This is the foundation for autonomous retail execution: systems that don’t just report on what happened, but actively decide what should happen next - which offers to show, when to show them, and how to maximize outcomes in real time.

Today, 1600+ brands and 5M+ consumers use Aisle to drive measurable results in brick-and-mortar. Under the hood, that means high-volume event ingestion, real-time decisioning, and infrastructure that has to be both reliable and low-latency to influence behavior in the moment.

We’ve gotten here with a small, fast-moving team, and now we’re scaling the system to handle significantly more volume, complexity, and automation - including AI systems that are part of the production path, not just offline analysis.

You’ll win here if…

What is Aisle?

Physical retail has always been a black box - brands ship product, run static promotions, and wait weeks (or months) to understand what actually happened.

You enjoy communicating across technical and non-technical teams looking to build shared understanding that can turn into collaborative actio
Can solve problems in stages with appropriate level of urgency when needed: immediate triage, temporary patch, and long term fix that increases durability of the system
You’re comfortable moving quickly, shipping improvements, and iterating in production
AI is a core part of how you work - you’ve gone well beyond basic copilots and actively use AI tools to design, debug, and ship systems faster
You treat AI agents as chaotic, untrusted components - your instinct is isolation, rate limiting, and permissions scoping, etc. (gist of harness engineering)
You have experience building or orchestrating AI/agent workflows - in production or through serious side projects

About your role

Reliability & Infrastructure

Own the reliability, scalability, and observability of our infrastructure across GCP and Vercel
Design and implement monitoring and alerting in Datadog, including monitors-as-code and product-level dashboards
Manage IAM, service accounts, and security best practices across our cloud environment
Participate in on-call rotation, incident response, and post-mortems — and turn learnings into systemic improvements

Core Infrastructure & State

Stabilize core infrastructure and stateful systems under heavy concurrent load from both consumer traffic and agent-driven workflows
Build and maintain our event-driven GCP infrastructure, including Cloud Functions, Pub/Sub, Workflows, and GKE/Kubernetes deployments
Investigate performance inconsistencies (e.g., identical replicas behaving differently) and drive durable root-cause resolution
Stabilize and simplify parts of the stack that create friction today (e.g., Prisma, connection management, cron workflows)
Automate infrastructure provisioning, deployments, and operational workflows

AI & Next-Gen Tooling: Agent Ops

Build agent operations infrastructure that enables AI agents to run safely and reliably in production
Develop secure isolation layers, LLM gateways, workflow monitoring, anomaly detection, and production telemetry
Help define CI/CD for an agent-driven engineering environment - including how code gets shipped, reviewed, validated, and deployed when agents are in the loop
Own visibility into AI usage, reliability, and spend as our agent footprint scales

Cross-functional Impact

Partner closely with engineering and product teams to maintain reliability without slowing development velocity
Act as a force multiplier across the team — helping engineers ship faster and more safely

About your skillsMust haves

4+ years in SRE, DevOps, or infrastructure/platform engineering
Strong, hands-on experience with a major cloud platform (preferable GCP)
Experience with event-driven or serverless systems (Pub/Sub, Cloud Functions, etc.)
Solid understanding of IAM, security, and cloud best practices
Experience with observability tools like Datadog
Familiarity with Node.js environments
AI is part of your daily engineering workflow you use AI tools thoughtfully to improve engineering velocity, reliability, and operational excellence beyond basic code generation.
Experience building or orchestrating AI/agent workflows (work or serious personal projects)
High ownership, strong curiosity, and a bias toward action

Nice to haves

Experience with harness engineering patterns for untrusted agents, including isolation, rate limiting, permission scoping, auditability, and safety controls
Familiarity with OpenClaw, agent orchestration frameworks, or LLM gateway patterns is a plus
Hands-on experience with GCP Workflows for orchestration
Familiarity with Prisma, pgbouncer, and PostgreSQL connection pooling
Experience with Vercel deployment and edge computing
Familiarity with the k8s ecosystem
Familiarity with Redis and BullMQ
Understanding of SOC 2 compliance requirements and implementation
Previous experience in a high-growth startup environment
Previous backend engineering experience to bridge the gap between infrastructure and code