Platform Engineer — Evolis AI

Rensora AI; United Kingdom; Remote; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Remote-first

Deep technical work

Equity

Learning budget

Cutting-edge AI systems

Job summary

Rensora AI is seeking a Platform Engineer to build the core infrastructure powering its AI agentic lifecycle platform. You will design distributed systems, implement CI/CD pipelines, and ensure secure, scalable operations across cloud environments.

You will collaborate with ML engineers and product teams to meet strict SLAs, multi-tenant isolation, and zero-downtime deployments. Remote-first culture with enterprise-scale responsibilities awaits.

Qualifications

• 4+ years in platform/infrastructure engineering or backend systems.
• Go or Python production distributed systems experience.
• Kubernetes deployment, networking, resource management and troubleshooting.
• Terraform and cloud (AWS preferred).
• Event-driven architectures with Kafka/NATS/RabbitMQ.
• Relational DBs (PostgreSQL) and caching (Redis) in production.
• Observability: Prometheus, logs, traces; SLO-driven ops.

Responsibilities

• Design core platform services for Evolis AI, including orchestration and state management.
• Build and maintain Kubernetes-based infra with Terraform for multi-cloud deployments.
• Develop event-driven architectures using message brokers to support real-time workflows.
• Implement comprehensive observability and alerting to meet enterprise SLAs.
• Design CI/CD pipelines with safe, auditable deployments and canary releases.
• Ensure multi-tenant isolation and security boundaries for compliance.

Tools

Kubernetes

Terraform

Kafka

NATS

RabbitMQ

PostgreSQL

Redis

Prometheus

ELK/Loki

SLO

Job description

Build and scale the infrastructure powering Rensora's AI agentic lifecycle platform.

As a Platform Engineer on the Evolis AI team, you will build the foundational infrastructure for Rensora's AI agentic lifecycle management platform. Evolis AI enables enterprises to deploy, manage, and govern AI agents across their operations — and your work will ensure the platform is fast, reliable, and secure at scale. You will design distributed systems, build robust CI/CD pipelines, implement comprehensive observability, and architect the event-driven backbone that powers agentic workflows.

You will work closely with ML engineers, product teams, and forward deployer engineers to ensure the platform meets the demanding requirements of enterprise clients — from strict SLAs and compliance mandates to multi-tenant isolation and zero-downtime deployments. Your decisions about infrastructure, tooling, and architecture will directly shape the reliability and performance characteristics of the platform.

This role is ideal for engineers who care deeply about building systems that are correct, observable, and operable. You will have significant ownership over technical decisions and the freedom to choose the right tools and patterns for each problem. If you want to build platform infrastructure that runs mission-critical AI systems for large enterprises, this is the role.

What You'll Do

• Design and implement the core platform services for Evolis AI, including agent orchestration, workflow execution, and state management
• Build and maintain Kubernetes-based infrastructure with Terraform, ensuring reproducible and auditable deployments across cloud environments
• Develop event-driven architectures using message queues and streaming systems to support real-time agentic workflows
• Implement comprehensive observability — metrics, logs, traces, and alerting — to ensure the platform meets enterprise SLAs
• Design and build CI/CD pipelines that support rapid, safe deployments with automated testing, canary releases, and rollback capabilities
• Architect multi-tenant isolation and security boundaries to meet enterprise compliance and data governance requirements
• Optimize database performance and data layer architecture for high-throughput, low-latency access patterns
• Participate in on-call rotations and incident response, driving root cause analysis and implementing preventive measures

What We're Looking For

• 4+ years of experience in platform engineering, infrastructure engineering, or backend systems development
• Strong proficiency in Go or Python, with experience building production distributed systems
• Deep hands-on experience with Kubernetes — including deployment strategies, networking, resource management, and troubleshooting
• Experience with Infrastructure as Code tools, particularly Terraform, and cloud platforms (AWS preferred)
• Solid understanding of event-driven architectures, message brokers (Kafka, NATS, or RabbitMQ), and gRPC
• Experience with relational databases (PostgreSQL) and caching layers (Redis) in production environments
• Strong understanding of observability practices — metrics (Prometheus), logging (structured logging, ELK/Loki), and distributed tracing
• A reliability-focused mindset with experience in incident management, postmortems, and SLO-driven development

Nice to Have

• Experience building platforms for AI/ML workloads, including GPU scheduling and model serving infrastructure
• Familiarity with service mesh technologies (Istio, Linkerd) and API gateway patterns
• Experience with multi-cloud or hybrid deployments, including air-gapped and on-premises environments
• Background in platform security — network policies, secrets management (Vault), RBAC, and audit logging

Why Rensora

• Remote-first, async culture
• Deep technical work — not ticket factories
• Competitive compensation and equity
• Continuous learning budget
• Work with cutting-edge AI systems at enterprise scale