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Connect is a Node CLI and a signed tray app for macOS, Windows and Linux. It points a developer's AI coding tools at our gateway by writing each vendor's own config, signs them in, keeps their credentials fresh, and repairs itself when something drifts. For IT, it ships the artifacts they need to roll it out across a fleet.

It's real, it's shipping, and customers are using it. You'd own it.

03What you'll do
Own Connect. The CLI, the tray app, updates, docs, and what ships next.
Write into other apps' config without breaking them. Back up what you touch, roll back cleanly, and never leave someone's setup worse than you found it.
Keep up with vendors. Config shapes change under us. Check before writing, and fall back to a manual path instead of guessing.
Stay clear of antivirus. Persistence and credential helpers are exactly what EDR watches for. Measure what actually trips a scanner instead of assuming.
Ship for managed fleets. Profiles, policy, credential helpers, and silent rollout. That's what an admin needs to push this to a few hundred laptops at once.
Make it debuggable from far away. Health checks, repair commands, and diagnostics that carry metadata only. Never prompts, never keys.

What You Will Be Doing
Own the co-build agenda with AWS & GCP
Drive our active co-build initiatives with AWS/GCP product and engineering teams from scoping through launch.
Own the technical relationship with AWS/GCP product managers and engineers on the EKS/GKE, Karpenter, and container services teams. Be the person they call, and the person who can answer without scheduling a follow-up.
Track the EKS/GKE and AI/ML roadmap closely enough to tell us what it means. Dynamic Resource Allocation, MIG and time-slicing landing in Karpenter and Auto Mode/Auto Pilot, managed control plane work, and pod isolation all move the ground under our product. You will be the first person to see it coming.
Continuously validate that we run on where AWS/GCP are going, not just where it is. As AWS/GCP abstracts the node further, our agent, our scheduler, and especially our GPU device plugin need to keep working. Confirming that, early, is a standing part of the job.
Bring AWS/GCP requirements and constraints back into R&D as real engineering input, and represent our architecture back to AWS/GCP accurately enough that they design around it.
Look for opportunities to be a design partner and later a launch partner.
Technical depth on us and EKS/GKE
Be the person who can explain how we work on EKS/GKE to any technical audience, without an SE in the room: real-time pod right-sizing, HPA and replica management, intelligent pod placement, Karpenter and node optimization, Spot, and GPU fractionalization and right-sizing for inference workloads.
Hold your own with AWS/GKE Solutions Architects and customer platform engineers on scheduling, autoscaling, resource management, and where our approach differs from static MIG and time-slicing.

We're looking for a Researcher who thrives on exploring the technical frontier and translating complex insights into real-world impact. This is a hands-on role, combining deep research with prototyping and cross-team collaboration, with the goal of driving innovation in Kubernetes internals, cloud infrastructure, and performance optimization.

Conduct deep research into Kubernetes internals, scheduling, autoscaling, and container resource usage.
Explore cutting-edge strategies for cloud resource optimization, cost efficiency, and performance engineering.
Design and deliver hands-on POCs, simulations, and benchmarks to validate new approaches.
Work closely with product and engineering teams to translate research findings into features and enhancements.
Stay at the forefront of the cloud-native and FinOps ecosystems, surfacing trends and opportunities.
Contribute to technical blogs, white papers, and internal knowledge sharing.

We're looking for a DevOps / Platform Engineer to own our infrastructure end to end- both sides of it.
Side one is our multi-tenant SaaS on AWS: you build it, you run it, you keep it fast, secure, and up. Side two is the part that makes this role unusual - our enterprise customers deploy Avon AI inside their cloud (and sometimes fully air-gapped, on-prem environments). You'll own that too: packaging the platform, running the installation with the customer's infrastructure and security teams, and being the person on the call when their environment doesn't look like anyone's reference architecture.
This is a customer-facing engineering role. You'll be in rooms with enterprise IT, security, and platform teams- walking them through our architecture, answering security review questions, and unblocking deployments. If you want a pure behind-the-scenes infra job, this isn't it. If you like owning infrastructure and being the trusted technical voice in front of a customer, read on.
You'll be our first dedicated DevOps hire, which means you inherit real systems in production and a lot of room to shape how they evolve.
Key Responsibilities
EKS, networking, data stores, CI/CD, cost, and uptime. Build and evolve it with Infrastructure as Code.
Maintain and improve our Helm charts and container distribution so Avon AI installs cleanly in a customer's Kubernetes cluster.
Plan and execute installations in customers' private clouds and on-prem/air-gapped environments, working hands-on with their infrastructure teams from kickoff through go-live.
Support security reviews and architecture discussions, and translate enterprise IT constraints back into our roadmap.
IAM, network segmentation, secrets management, WAF, and the controls enterprise customers audit us on.
Metrics, logs, tracing, and alerting for our SaaS, and self-contained monitoring for customers who won't ship telemetry outside their network.
CI/CD pipelines, ephemeral PR sandboxes, release automation, and local development so engineers ship quickly and safely.
For our SaaS tenants and for deployed customer installations, including on-call ownership of what you build.

We are seeking a highly experienced, AI-obsessed AI Senior Backend Engineer to join our core Engineering department. In this newly created, cross-functional role, you will be the driving force behind the companys internal AI transformation. You will act as the responsible for artificial intelligence, architecting, building, and deploying custom AI and automation systems from scratch to empower various departments and streamline operations.
Key Responsibilities
Architect, develop, and deploy tailored AI systems and applications from the ground up to solve organizational challenges.
Identify process bottlenecks across different teams and design robust backend automation solutions to optimize daily workflows.
Lead the hands-on integration of modern Generative AI models, APIs, and frameworks into the company's internal infrastructure.
Build scalable, high-performance backend microservices and APIs to support heavy data processing and AI workloads.
Act as the technical AI focal point, partnering closely with internal stakeholders and department heads to gather requirements and deliver high-impact technological solutions.
Collaborate with product, DevOps, and other teams to ensure that AI solutions are aligned with user needs and business goals.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across our platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose our capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how we evolve from AI-enhanced internal tools to customer-facing AI products.

What You'll Be Doing
Engage with customers to ensure their success.
Partner with the sales team to drive the customer journey, build technical wins, and grow champions.
Develop a deep understanding of customers' goals and objectives, and articulate how our offering addresses their needs.
Create and own value-based relationships at all levels within customer organizations.
Actively participate in all phases of planning and execution, from initial discovery to the technical win.
Develop and maintain deep product expertise to demonstrate the value of us in sales meetings and at events such as meetups and conferences.
Advise the sales team on effective ways to position our product.
Onboard, educate, and enable partners, and support them through sales cycles.
Continuously develop your sales and technical skills through self-driven learning and our professional development opportunities.

Were looking for our next Manager, Cybersecurity Engineering. Could It Be You?
As the Manager of Cybersecurity Engineering, you will lead and grow a team of security architects dedicated to embedding security into our engineering culture in alignment with our regulatory compliance requirements as a Financial Services provider. Reporting to the Director of Cyber Strategy & Risk, you will own the team's technical direction and its impact on the organization's overall security posture - spanning architecture oversight and threat modeling, legacy system risk, security guardrails and automation, and M&A security diligence. You will balance technical leadership with people management, establishing your team as a trusted consultative partner that enables safe innovation across cloud-native financial platforms, legacy systems, and corporate integrations.
The Manager, Cybersecurity Engineering is a champion for putting the customer first and has a deep passion in understanding customer behaviour. They will create lifecycle journeys to improve the customer experience, engagement and retention as we deliver on our promise to help customers keep more of their money as they become more financially successful and secure.

We are a well-funded, early-stage startup, looking for a talented and motivated AI Engineer to join our team.
The focus of this role is to develop advanced AI agents aimed at automating and optimizing low-skill human tasks, with a special emphasis on document processing, data extraction, text and email comprehension, and related workflows.
You will be responsible for researching, designing, and deploying AI solutions that can replace repetitive manual tasks, improving efficiency and scalability for organizations.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer to join our founding team. The focus of this role is to design, develop, and deploy autonomous AI agents that can automate and optimize complex enterprise workflows.
You will work on building intelligent systems capable of decision-making, data extraction, document processing, and other tasks typically requiring human intervention.
This is an opportunity to influence the architecture and strategy of AI-driven automation solutions for large-scale enterprise environments.

We are a well-funded, early-stage startup looking for a Frontend / Fullstack Engineer to join our founding team. In this role, you will help build cutting-edge web applications and platforms that bring autonomous AI agents to life, automating complex enterprise workflows. You will play a critical role in shaping intuitive, responsive UIs and robust backend APIs that connect AI-driven agents to real-world enterprise systems (ERP, CRM, and more).
This is an opportunity to influence the architecture, design, and user experience of next-generation AI-powered automation solutions for large-scale enterprise environments.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team.
The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows.
You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.