Careers at Epsilon ASI
Our work starts with the real artifacts of engineering: architecture notes, pull requests, runbooks, dashboards, incidents, and the constraints teams face every day. We make that context visible, then help turn it into systems that are clearer, stronger, and easier to operate.
We work from artifacts
Architecture notes, pull requests, runbooks, dashboards, incidents, and the actual constraints your team works inside.
We make context visible
The block gives the page more texture without making it feel like a stock-photo agency site.

PRs, notes, and delivery context

Pressure map workshop

Artifacts your team keeps
Embark on a rewarding journey with us. Find opportunities to grow, learn and make a lasting impact.
Join a team that embraces forward-thinking ideas, fosters innovation, and cultivates an environment where your creativity can flourish.
We think deeply about the real-world impact of every solution on teams, customers, and stakeholders.
Our work is grounded in best practices, thoughtful design, and sustainable engineering.
We’re invested in outcomes that endure, not quick fixes that falter.
Hiring journey
The interview path should feel like the work: clear communication, systems thinking, technical judgment, and the ability to collaborate without ego.
01
Intro conversation
A lightweight conversation about your background, what you want next, and the kinds of platform problems you like solving.
02
Systems discussion
Walk through a real platform scenario and talk about tradeoffs, sequencing, observability, reliability, and team enablement.
03
Working session
Pair on a small practical exercise or artifact: architecture notes, implementation plan, review, or operational improvement.
04
Mutual fit
Discuss role shape, expectations, compensation, client work, team norms, and how you do your best engineering work.
What working here should feel like
The benefits are designed around focus, trust, craft, and the reality that deep engineering work needs room.
Deep work time
Room for architecture, implementation, writing, review, and careful technical judgment.
Senior peer group
A team that values context, humility, strong opinions, and better systems.
Client impact
Work directly on the platform constraints that are slowing real engineering teams down.
Craft and learning
Kubernetes, cloud, modernization, AI workflows, and delivery systems in production contexts.
Secure defaults
We care about secrets, access, change safety, auditability, and operational guardrails.
Modern tools
Use automation and AI carefully, with bounded context and human approval.
No mystery process, no puzzle interviews.
Be a part of a winning culture that fosters collaboration, creativity, and success in every career path
A Senior Platform Engineer at Epsilon ASI designs, builds, and maintains the core infrastructure and tools (like cloud services, CI/CD, and automation) that enable development teams to build and deploy software efficiently, while also mentoring others and setting technical strategy for platform reliability, scalability, and developer experience.
Our Client Success Lead drives customer loyalty and revenue growth by overseeing a team that ensures clients achieve their goals, building strong relationships, and strategically enhancing product adoption and retention through proactive support and cross-functional collaboration
A Head of Growth Operations at Epsilon ASI builds and optimizes the systems, processes, and data infrastructure that power sustainable business expansion, blending marketing, product, and analytics to drive customer acquisition, activation, retention, and revenue through scalable strategies and cross-functional execution
DevOps and platform engineering overlap, but they do not solve the same bottleneck. Use DevOps to clarify ownership and feedback loops. Use platform engineering to reduce cognitive load through self-service. The hard part is diagnosing which problem you actually have.
Human review should be a control, not a default layer. Use a simple taxonomy to decide which AI workflow steps stay automated, which escalate, and which should stop until a human with real authority takes over.
Agent workflows can look fine while the plan, tool use, or policy path regresses. This guide shows how to build an eval harness around scenarios, golden tasks, tool traces, and acceptance thresholds—and keep it current as the workflow changes.
A practical framework for bringing cloud economics into architecture review without turning it into a finance gate: name the dominant cost driver, surface hidden spend, and make reliability-vs-spend tradeoffs explicit.