Thesis: Agentic AI-Ops: Autonomous AI Agents for Production Infrastructure

Knightec Group

Sundsvalls kommun

On-site

SEK 167,000 - 212,000

Full time

5 hours ago
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Job summary

Knightec Group in Sundsvall invites Bachelor/Master students to undertake a thesis project focused on AI agents connected to real infrastructure via the Model Context Protocol (MCP). The work investigates levels of autonomy in a production‑like Kubernetes/Jira environment.

You will build a small isolated environment, connect AI agents to it, evaluate graded autonomy levels, simulate failures, and compare AI‑generated Jira tickets against human incidents, under supervision.

Qualifications

  • Bachelor or Master degree in Computer Science/Engineering.
  • Graduation expected in June 2027.
  • Fluent in Swedish and English, written and spoken.

Responsibilities

  • Build a small isolated environment (Kubernetes cluster and Jira board) and connect AI agents via MCP.
  • Evaluate autonomy levels: observe/filing, propose/approve, autonomous actions within safe bounds.
  • Inject controlled failures and compare agent diagnoses, actions, and generated tickets to human baselines.
  • Document guardrails and permission models for safe integration into DevOps workflows.

Skills

Fluency in Swedish
Fluency in English
Academic research

Education

Bachelor/Master of Science in Computer Science/Engineering
Graduation in June 2027

Job description

High Level Description

AI agents connected to real infrastructure via the Model Context Protocol (MCP) or such, can already read live system state and take real action, such as scaling a Kubernetes deployment, restarting a pod, or filing a Jira ticket. What is still an open question is how much autonomy such an agent can safely be given in a production‑like environment before the risk of an incorrect action outweighs the benefit of speed. This thesis investigates this question in a sandboxed environment built by the student.

High Level Description

AI agents connected to real infrastructure via the Model Context Protocol (MCP) or such, can already read live system state and take real action, such as scaling a Kubernetes deployment, restarting a pod, or filing a Jira ticket. What is still an open question is how much autonomy such an agent can safely be given in a production‑like environment before the risk of an incorrect action outweighs the benefit of speed. This thesis investigates this question in a sandboxed environment built by the student.

Project Description

The student builds a small, isolated environment (a Kubernetes cluster and a Jira board) and connects AI agents to it via MCP tool calls (or something else). The agent is evaluated across a set of graded autonomy levels, from observing and filing tickets in Jira to proposing actions for approval to acting autonomously within tightly scoped, low‑risk operations. Controlled failures (pod crashes, resource exhaustion, network faults) are injected, and the agent’s diagnoses, proposed or executed actions, and generated tickets are compared against a human baseline.

Who are we looking for?
  • Bachelor/Master of Science in Computer Science/Engineering
  • Graduation in June 2027
  • Fluency in Swedish, both written and spoken
  • Fluency in English, both written and spoken
Purpose

Bachelor students typically focus on one question; master students take a broader comparative evaluation. In this thesis, investigate these questions:

  • How does the level of autonomy granted to an AI agent (observe-and‑escalate vs. propose-and‑approve vs. autonomous‑within‑bounds) affect the accuracy and safety of its actions in a simulated Kubernetes/Jira environment?
  • How accurately can an LLM‑based agent diagnose the root cause of an injected infrastructure fault compared to a human operator, and how is that accuracy measured objectively?
  • How useful and accurate are automatically generated Jira tickets (context, root‑cause hypothesis, affected services) compared to tickets written by a human on the same incidents?
  • What architecture, guardrails and permission model (e.g. Kubernetes RBAC) are needed to safely integrate such an agent into an existing DevOps workflow?
An Exciting Journey with Knightec Group

Semcon and Knightec have joined forces as Knightec Group. Together, we are Northern Europe’s leading strategic partner in product and digital service development. With a unique combination of cross‑functional expertise and a holistic business understanding, we help our clients realize their strategies – from idea to complete solution.

Practical Information

This is a thesis position, located at our office in Sundsvall. Start date January or March 2027.

no later than 2026-11-30.

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