AI Engineer & Senior AI Engineer (Applied AI Systems)

About Combient

Combient Group brings together leading large companies in the Nordics on the digitalization journey. We are convinced that collaborating across industries helps us move smarter and faster. Our network collectively includes 36 large enterprises 1.4 million employees and 270 billion in revenue.

As AI technologies proliferate rapidly long-standing business operating assumptions are being fundamentally reshaped. We are the first generation of leaders navigating this transition in real response AI @ Combient brings together initiatives and services that help companies move from uncertainty to capabilitythrough learning strategic advisory and practical interpretation of fast-evolving technology. Within this ecosystem the Combient AI Center is a newly established applied research arm that combines deep technical expertise with the informed judgment that comes from hands-on building.

Our 2026/2027 roadmap involves three streams of work in collaboration with our network to generate both evidence and product for our companies including

• controlled experimental study focused on engineering-agent collaboration
• fast prototyping cycles to evaluate emerging ideas in generative and agentic systems and
• AI product engineering to address challenges we have surfaced from the network of companies.

We focus on the collective priorities and challenges of the network by building real systems testing them in live organizations and scaling successful pilots into sustained operating capabilities.

The Role

Were hiring an AI Engineer and Senior AI Engineer to join the Combient AI Center in Stockholm.

This role is for someone who enjoys working where research meets production: designing experiments building prototypes that generate evidence and turning the strongest concepts into results into production outcomes reusable products and evidence that teams and leaders can rely on.

Youll work at the intersection of:

• LLM systems (RAG tool calls agents) and evaluation
• Data evaluation infrastructure
• Human-in-the-loop system design
• Enterprise constraints (privacy governance security incentives)

The work is hands-on collaborative and social by design. Youll build things with people from multiple companies always with shared ownership of the outcome.

What Youll Do

You will contribute to and/or lead work such as:

• Design and run applied studies of AI systems in real workflows (define hypotheses baselines success metrics and instrumentation).
• Build evaluation and telemetry infrastructure to measure outcomes like productivity rework quality maintainability and trustwithout relying on vanity metrics.
• Develop agent-assisted workflows and prototypes that can be tested under constraints (reviews CI/CD security boundaries approval processes).
• Create reference implementations and how-to patterns that member companies can adopt with confidence.
• Collaborate closely with researchers and social science/UX partners to connect technical signals with human behavior and organizational realities.
• Communicate findings through internal writeups demos and practitioner sessions

What Were Looking For

You dont need to tick every box but we look for candidates who have a growth mindset and can adapt to the moment. Most strong candidates will have:

• Strong software engineering fundamentals (Python production systems).
• Hands-on experience with shipping LLM-backed products retrieval monitoring.
• Comfort with experimental thinking: measurement design baselines confounders and iteration.
• Experience building robust data pipelines / logging / observability for AI products.
• Ability to operate in ambiguity and collaboratively define the right problem.

You enjoy collaborating sharing and building things others can actually use.

Bonus Points

• Experience in developer tooling CI/CD or workflow instrumentation
• Experience in regulated environments or privacy-preserving data practices
• Publications are welcome but not required (we care that you can produce credible evidence not just PDFs)

How We Work

• We value respectful debate and evidence-based decisions
• We compare and contrast approaches make trade-offs explicit and time-box discussion
• Once we decide we align and execute with shared ownership

Why This Role Is Different

• Your work wont end at a demo: youll generate evidence and turn it into reusable systems.
• Youll collaborate across multiple large organizations so your impact compounds.
• Youll help shape what responsible measurable AI adoption looks like in practice.

Practicalities

• Hybrid work arrangement based in Stockholm Sweden
• Occasional travel to member companies in Nordics
• Strong peer group across engineering product and research/social science
• High autonomy and influence over technical direction