Senior AI / Platform Engineer

Basic Information

• Role: Senior AI / Platform Engineer
• Start Date: August
• Assignment Duration: Until end of the year (2026)
• Location: Stockholm - hybrid setup

Project Information

Project Description (overview of the project and its objectives):

The team is the central hub for AI enablement and developer productivity across the organization. The assignment is not about building AI product features, but about increasing AI adoption through shared platform capabilities, governed LLM/MCP integrations, reusable AI skills, agents, and automations. The objective is to make AI capabilities easier, safer, and more productive for engineering and non-engineering teams to adopt.

Team Structure (who the consultant will work with):

The consultant will work within the developer-enablement function in the Foundation organization, together with Platform Services, Information Security, NOC, Data Platform, and product engineering teams consuming the AI/MCP platform.

Consultant Profile & Requirements

Key Competencies & Technologies

Mandatory: Hands-on agentic development using tools such as Claude Code, Cursor, Codex, Aider, or similar; strong prompt engineering; experience with AI agents, AI skills, MCP servers, LLM gateways, and MCP gateway concepts such as routing, governance, cost control, auditability, and tool federation. Strong software engineering experience with Go, Java, AWS EKS/RDS, GitHub Actions, and production-grade cross-system automations is required. The consultant should be collaborative, self-organized, and able to contribute to RFCs, technical designs, and documentation. We are looking for someone who shares ideas, reduces cognitive load for engineers, and balances short-term delivery with long-term platform direction.

Preferred: Python, embeddings, semantic search/vector databases, Kubernetes, Helm, GitOps, TypeScript, Okta SCIM/OIDC, Datadog, Slack Bolt, compliance-as-code, and AI security topics such as prompt injection, tool poisoning, and scope abuse.

Years of Experience: 7+ years of software engineering experience, including proven practical work with LLMs, agents, automations, or AI-enabled developer workflows in production or production-like environments.

Languages: English, fluent written and spoken. Swedish is a plus.

Responsibilities

Daily Tasks: What will the consultant be working on?

The consultant will work on initiatives that improve developer productivity, platform reliability, and AI adoption across product teams. This includes identifying common friction points in engineering workflows, building tools and automations that help teams move faster, and enabling teams to use AI safely and effectively in their daily work. The consultant will collaborate with product teams, platform teams, and security stakeholders to reduce dependencies and handovers between teams, improve self-service capabilities, and make deployment and operational workflows easier to use. The work will include building and improving internal AI tools, MCP-based integrations, reusable automations, documentation, onboarding material, and platform capabilities that help teams release more independently, frequently, and confidently.

Deliverables: Expected outcomes/deliverables in the role.

The expected outcome is higher deployment frequency, reduced dependency and deflection across product teams, and increased availability of company products through better platform enablement and AI adoption. Deliverables may include self-service tools, AI agents, MCP servers, reusable automations, improved onboarding flows, RFCs, documentation, observability improvements, governance controls, and adoption support for product teams.