• Own the architecture and evolution of P2P.org's internal developer platform—Kubernetes, monitoring, secrets management, and delivery infrastructure. You are responsible for how these systems scale, interconnect, and evolve across 60+ blockchain networks. • Design and build scalable, fault-tolerant platform components—including capacity planning, multi-tenancy, networking topology, and storage architecture. Make and document architectural trade-offs clearly. • Write production code in Go and/or Python — platform tooling, services, operators, and APIs. This is a hands-on engineering role, not just configuration. • Build self-service infrastructure that teams consume with minimal friction — Terraform modules, Helm charts, reusable pipeline templates, and platform APIs. Champion our versioned module library and automated security propagation via Renovate. • Scale our Kubernetes platform across bare-metal and cloud, and evolve the observability stack (Victoria Metrics, Prometheus, Grafana, Loki) and delivery platform (ArgoCD, CI/CD pipelines). • Own the security posture of the platform — secrets management, access controls, identity federation, network policies, and encryption at rest and in transit. • Maintain SOC 2 Type II compliance across platform infrastructure — implement controls as code, maintain audit readiness, and work with compliance teams to close gaps proactively. • Enforce container and supply chain security — image scanning, signed artifacts, base image management, and vulnerability remediation. Apply zero-trust principles: least-privilege roles, short-lived credentials, auditable access. Harden Kubernetes workloads through pod security standards, network policies, RBAC, and runtime monitoring. • Use AI tooling as a core part of how you work and champion its adoption across the infrastructure team and wider engineering organization—in code generation, code review, incident response, documentation, and operational automation. • Build or integrate AI-assisted tooling into platform workflows where it delivers genuine improvement. Help define how we measure the impact of AI adoption across engineering. • Lead the technical direction for the infrastructure team—set architectural standards, drive best practices, and reduce technical debt. • Collaborate cross-functionally with SRE, blockchain, engineering, data, and security teams. Translate their needs into platform capabilities. • Mentor and grow engineers through code reviews, architectural guidance, design reviews, and knowledge sharing. • Contribute to incident response and post-incident reviews, driving platform reliability improvements.

This is a job that Jill, our AI Recruiter, is recruiting for on behalf of one of our customers. She will pick the best candidates from Jack's network The next step is to speak to Jack. Job Title: Senior Platform Engineer (DevSecOps) Company Description: 9fin.com - Series C AI platform for debt markets Job Description: Join 9fin's high-seniority Platform team to lead the security function from the ground up. You will design and implement the automated guardrails, policy-as-code, and secure-by-default systems that allow engineers to move fast while protecting a platform used by 300+ blue-chip institutions across the $145 trillion global debt market. Location: Remote, UK Why this role is remarkable: - Opportunity to build a security function from a "cold start," defining the standards, tooling, and culture for a unicorn-stage fintech. - 9fin just closed a $170M Series C at a $1.3B valuation, providing massive growth trajectory and stability with 300+ institutional clients. - Work in a high-autonomy, low-ego environment within a senior Platform team that functions as an internal product group rather than a ticket-based service. What you will do: - Design and implement automated security guardrails across a multi-account AWS environment using Terraform and policy-as-code. - Build and maintain secure CI/CD pipelines in GitHub Actions, including secret scanning, dependency analysis, and build integrity checks. - Partner with the Head of InfoSec to translate SOC 2 compliance requirements into pragmatic, engineering-led platform features and automated gates. The ideal candidate: - Proven experience owning or significantly improving cloud security posture, ideally building security functions from scratch in a startup/scale-up environment. - Expert-level proficiency with AWS, Infrastructure as Code (Terraform), and modern application security patterns like decentralized authentication. - Strong communicator who can balance security requirements with developer experience to influence engineering teams across the entire organization. Who are Jack & Jill? Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support. And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate. Next steps Step 1. Visit our website. Step 2. Click 'Talk to Jack'. Step 3. Talk to Jack so he can understand your experience and ambitions. Step 4. Jack will make sure Jill (the AI agent working for the company) considers you for this role. Step 5. If Jill thinks you're a great fit and her client wants to meet you, they will make the introduction. Step 6. If not, Jack will find you excellent alternatives. All for free. We never post fake jobs This isn't a trick. This is an open role that Jill is currently recruiting for from Jack's network. Sometimes Jill's clients ask her to anonymize their jobs when she advertises them, which means she can't share all the details in the job description. We appreciate this can make them look a bit suspect, but there isn't much we can do about it. Give Jack a spin! You could land this role. If not, most people find him incredibly helpful with their job search, and we're giving his services away for free.

THE COMPANY Gatekeeper is a SaaS-based, next-generation Vendor & Contract Lifecycle Management platform. We help organisations reduce risk, improve compliance and maximise value. As part of our journey to becoming an AI-first company, we are embedding AI agents deeply into how Gatekeeper operates internally. These agents are not experiments; they actively support decision-making, approvals, reviews and operational workflows across the business. We’re hiring AI Platform Engineers to accelerate this transformation by working directly with teams to implement, integrate and maintain AI agents at scale. THE ROLE The AI Platform Engineer is a hands-on, execution-driven role focused on deploying AI into real business workflows. You will help shape our internal AI platform and agent frameworks and apply them inside the organisation. You will work closely with our Senior AI Platform Engineer, acting as the bridge between AI capability and day-to-day business execution. This role suits someone who is technical, pragmatic and product-minded. WHAT YOU’LL DO - Implement and deploy AI agents into internal Gatekeeper workflows. - Work directly with internal teams (Product, Marketing, Finance, Sales, Account Management, Operations, Professional Services) to understand processes and identify high-impact AI use cases. - Configure agent behaviour through prompts across different tools, rules and guardrails. - Integrate AI agents with existing systems, data sources and internal tools via APIs, webhooks and integrations. - Use Python for orchestration, data handling, light automation and evaluation. - Test, iterate and refine AI agents based on real usage and feedback. - Monitor deployed agents for accuracy, reliability and business impact, escalating issues where deeper platform changes are needed. - Collaborate with the Senior AI Platform Engineer on agent standards, tooling, observability, governance and ROI. - Document implementations and help establish repeatable internal AI deployment patterns.

• Design, implement, and deploy advanced AI capabilities within the OneAI platform. • Shape the end-user experience by designing intuitive workflows for model management, deployment configuration, and job operation. • Streamline the model lifecycle by integrating public repositories (e.g., Hugging Face) for seamless discovery, import, versioning, and deployment. • Bridge the gap between systems engineering and product design to ensure a seamless transition from backend infrastructure to user features. • Integrate cutting-edge AI frameworks and engines, such as vLLM, NVIDIA Dynamo and Unsloth, into a secure and scalable environment. • Leverage OpenNebula to orchestrate high-performance inference and training workloads across diverse cloud and edge environments. • Develop and maintain reliable APIs for compute provisioning and workload scheduling. • Implement GPU-aware operations to ensure optimal resource allocation and hardware utilization. • Build comprehensive observability suites to monitor and track critical metrics, including latency, throughput, utilization, and failure rates. • Establish and refine deployment and workflow strategies to ensure AI workloads remain efficient and stable at scale. • Optimize system architecture to balance high performance with cost efficiency. • Research and integrate emerging AI tools and engines to keep the OneAI platform at the forefront of the industry. • Analyze performance bottlenecks to iterate on the efficiency of both training and inference processes.