Conveo is the AI research platform enabling fast, affordable, and high quality consumer / B2B research. Global brands like Unilever, Google, and Orange use our AI video interviewer to across insights, marketing, and product teams.
What problem are we solving
The current/traditional research methods companies rely on are slow, expensive, and superficial. Running great research also requires expertise which is a blocker to many companies. That directly affects how well companies understand their customers and how well they can serve them.
The team you will join
You will join an extremely talented team of incredibly passionate, high-energy people. We go the extra mile while having the best time of our lives. Our team has the combination of decades of market research knowledge, incredible engineering ability, and experience building companies.
How we operate
We truly care about our clients and the problem we solve. That means we humbly go the extra mile every time. Our engineering team talks directly with our customers. No layers in between. We work hard and we have fun. To keep our quality bar incredibly high, we want to execute with the smallest possible team.
The Role
This is not a pure infrastructure role. We're looking for someone who is equally comfortable hardening a Kubernetes cluster, opening a PR on a product feature, and building internal tools that enables and support the product and engineering function — and who sees these activities as part of the same job. As a Senior Platform Engineer, you'll own the infrastructure and deployment platform that powers Conveo's AI research product. But you'll also shape how the engineering team builds — establishing the AI toolchain, workflows, and guardrails that let engineers move fast with agents and automation without flying blind.
What You'll Do
Platform & Infrastructure: Design, build, and maintain CI/CD pipelines for rapid, safe deployments with rollback capabilities.
Codify and manage cloud infrastructure using Infrastructure as Code (Terraform, Pulumi, or similar).
Own observability end-to-end — monitoring, logging, alerting — so the team has full visibility into production health.
Establish and improve incident response processes as we scale.
Ensure infrastructure practices meet SOC 2 and ISO 27001/27701 compliance requirements by design, not as an afterthought.
Engineering Platform & Developer Experience: Improve the day-to-day experience of shipping — local environments, tooling, review cycles, deployment ergonomics.
Contribute directly to the product where it matters: you're as comfortable with a feature branch as a Terraform plan.
Work with engineering leads to define and maintain standards as we grow from 8 to 18+ engineers.
AI Tooling & Governance: Standardise the engineering team's AI toolchain — model access, coding agents, MCP servers — so everyone operates from a shared, supported baseline rather than ad hoc setups.
Build and maintain reusable agent workflows and prompt libraries that encode engineering knowledge and compound over time.
Implement the guardrails and tooling controls that translate AI policy into practice — sandboxing, approved integrations, safe defaults — so engineers don't have to think twice about whether they're operating safely.
Evaluate and integrate new AI tooling as the ecosystem evolves, running adoption sprints that keep the team at the frontier without accumulating risk.
What We're Looking For
5+ years in a DevOps, SRE, platform engineering role.
Strong hands-on experience with CI/CD tooling (GitHub Actions, GitLab CI, or similar).
Infrastructure as Code in production (Terraform, Pulumi, or equivalent).
Solid cloud platform depth — AWS, GCP, or Azure. We value depth over breadth.
Containerisation and orchestration (Docker, Kubernetes, or similar).
Monitoring and observability (Datadog, Grafana, Prometheus, or similar).
Comfortable writing and shipping product code — you can open a PR on a feature, not just on infra.
Security-first instinct — you know compliance is designed in, not bolted on.
Experience with SOC 2, ISO 27001, or similar is a strong plus.
You're energised, not threatened, by AI agents doing things you used to do manually — and curious about where the boundaries actually are.
You think in systems: good defaults, guardrails, and leverage.
You'd rather make the safe path the easy path than police what people do.
Comfortable owning a domain end-to-end while staying closely collaborative — you know when to move independently and when to loop people in.
Excellent written and spoken English — you'll work directly with the CTO and across the engineering team.
