AI Harness Engineer

Description

AI Harness Engineer (Senior/Principal)

About the role

Weve had real wins with AI at Milestone but theyve mostly stayed inside the teams that found them. Were looking for someone to take whats working and build it into a platform the whole engineering organization can rely on.

The work sits in the layer around the models: the gateway agent tooling context handling evaluations guardrails observability and cost controls that make AI dependable for real engineering work. Youll own that layernot just run it but set the technical standards and reference architectures other teams build against.

The first phase is our internal development there youll bring the same rigor to the AI features going into our products working alongside the teams that own them.

Part of the job is being straight with us about where AI doesnt help not only where it does.

On level: were open at both senior and principal. At senior we expect you to build and operate this platform. At principal we additionally expect you to set the technical direction for AI-assisted engineering across the organization the person other staff and principal engineers argue with andcomeaway convinced by.

What youll do

• Own the AI engineering platform: the model gateway agent loops context handling tool integrations caching and guardrails along with the identity secrets handling and audit trails around them. This is production infrastructure serving the whole engineering organization with the availability and security expectations that implies.
• Define the technical standards and reference architectures for AI-assisted development: how teams integrate agents into their workflows what good looks like for context and evaluation which patterns we support and which we dont.
• Build the observability layer. Trace an agent run end to end so that when somethingfailswe can say whether it was the model the context the tool call or the code and act on the answer.
• Take the experiments already working somewhere in the company and turn them into something other teams can pick up and run with.
• Stand up the evaluations and cost tracking we need to tell whether a given tool is pulling its weight.
• Own the build-versus-buy recommendations. We should buy most infrastructure; the parts tied to our products or to our on-prem and compliance requirements are where building may make sense.
• Make it run where we run. On-prem and air-gapped deployment is a first-class design constraint here not an edge case.
• In the second phase work with product teams to bring the same approach to customer-facing AI features inside EU AI Act and GDPR.

• Get engineers on board the right way by showing them pairing with them and writing things down so the change outlasts you.

What youll bring

• Time spent as a staff engineer or senior IC building and operating distributed production systems: API and service boundaries failure modes under load observability and the security work that comes with handling credentials and sensitive source code.
• Real hands-on familiarity with todays AI coding tools (Claude Code Cursor Copilot Codex and the like) and the craft around them: context engineering prompting caching tool use memory and the rest of it.
• Experience putting an LLM-based system into production and keeping it there: evaluation failure modes latency cost and what breaks once real traffic arrives. Internal platforms count as production.
• Strong fundamentals. When an agent fails you can work out why and fix it rather than just file a ticket.
• A habit of treating token and compute spend as a real budget and a sense ofhow tobring cost-per-task down.
• Some history measuring this kind of work adoption quality productivity or ROI using frameworks like DX Core 4 or DORA.
• The presence to stand in front of experienced skeptical engineers have the hard conversation and still bring them with you.

• A view that AI is a powerfultoolbut that engineering judgment is what makes the difference plus enough curiosity to keep up as the field shifts.

Nice to have

• Youve shipped agentic features ina product customersactually use.
• Experience building or operating under EU AI Act or GDPR requirements.
• Youve run an internal model gateway LLM monitoring or evaluation tooling at organizational scale.

• Experience with on-prem or air-gapped deployments.

About the team

Youll join a new team in the Experience Development Organization set up to put Milestone on the front edge of AI-assisted development. The team is being built now: youll work alongside other AI Harness Engineers as it grows and closely with engineering teams across the organization.

What we offer

• Individual development plans aligned with your career goals
• Access to training learning resources certifications and professional development
• Flexible hybrid working arrangements
• Supportive leadership and regular feedback
• Opportunities for cross-functional and international collaboration
• A People First culture built on trust inclusion and empowerment
• Social activities and spaces to connect with colleagues across the organization

Practical details

Please note that applying for this position requires a valid Danish work visa.

We encourage you to submit your CV in English as soon as possible. Applications will be reviewed on an ongoing basis and the position will remain open until the right candidate has been identified.

At Milestone Systems we are committed to providing an inclusive and unbiased recruitment process where all employment decisions are based on qualifications experience and potential.

Application Process

Please note that applying for this position requires a valid Danish work visa.

We encourage you to submit your CV in English as soon as possible. Applications will be reviewed on an ongoing basis and the position will remain open until the right candidate has been identified.

At Milestone Systems we are committed to providing an inclusive and unbiased recruitment process where all employment decisions are based on qualifications experience and potential

About us

Milestone Systems is a leading provider of data-driven video technology software. Our portfolio includes XProtect video management softwareArculesvideo surveillance as a service andBriefCamanalytics. We amplify what organizations of any size can see do and achieve with video.

Guided by our People First mindset freedom inclusion and togetherness we always consider our employees partners and communities in everything we do.

Required Experience:

IC

Employment Type : Full-Time
Experience: years
Vacancy: 1