
AI Engineer
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Stockholm, Sweden"), this listing's salary midpoint is about 90% lower. The offer sits below the benchmark range (€3,904–€12,918). The listed pay band (€709–€997) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 13 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: AI Engineer | €10,128/per month | €12,298/per month | €14,468/per month |
| All roles in Stockholm, Sweden | €3,904/per month | €7,051/per month | €12,918/per month |
Epiminds is building the next generation of marketing systems. We’re live with 22 leading agencies managing 420 brands on a closed waitlist, with 1,300+ more waiting for access. Backed by a $6.6M Lightspeed-led round. Role Mission 🎯 Turn cutting-edge AI research and agentic systems into reliable, production-ready capabilities that empower Lucy and her team. You will design, implement and scale models, orchestration, and evaluation pipelines so our autonomous agents perform safely, efficiently and transparently in real customer workflows. Core Responsibilities Agent Development & Orchestration - Implement and iterate agent policies, task planners and chain-of-action orchestration. Improve how agents coordinate, delegate and surface their reasoning to users. Model Integration & Infrastructure - Integrate LLMs and multimodal models (inference and streaming) with robust, cost-effective serving infrastructure. Build observability into model usage, latency, and cost. Evaluation & Safety - Design automated and human-in-the-loop evaluation systems for agent performance, correctness and alignment. Implement safeguards, mitigation strategies and monitoring for risky behaviours. Data & Feature Engineering - Own pipelines for training, fine-tuning, retrieval-augmented generation (RAG) and vector search. Curate datasets and features that improve agent reasoning and factuality. Cross-functional Collaboration - Work closely with product, design and customer success to translate capabilities into memorable user experiences and measurable business impact. What We’re Looking For 3+ years working with production ML/AI systems, ideally with agentic or multi-agent architectures. Practical experience integrating LLMs and multimodal models (API-based or self-hosted) into applications. Strong software engineering skills (Python, TypeScript or similar) with production-grade system design and testing. Experience with retrieval systems, vector databases and feature stores preferred. Track record of shipping end-to-end systems: data, models, infrastructure and monitoring. Bias, safety and evaluation mindset — able to design metrics and mitigation strategies for real-world deployments. Collaborative, high-ownership approach and clear communication with cross-functional partners. Why Epiminds Epiminds is a small, high-ownership team built by people from Google and Spotify, backed by investors behind Anthropic, xAI, and Mistral. We’re building autonomous, multi-agent AI systems that represent the next evolution of marketing, not as a future vision, but in production today, used by agencies and brands at scale. What We Offer Competitive salary and meaningful equity. Healthcare, retirement savings, wellbeing support. Office catering. Recruitment Process Recruiter screening. Technical task. Code Interview. Trial with us in the office. Epiminds is an equal opportunity employer. We welcome applicants of all backgrounds and are committed to creating an inclusive environment for everyone.
Job Details
Responsibilities
- Agent Development & Orchestration - Implement and iterate agent policies, task planners and chain-of-action orchestration.
- Model Integration & Infrastructure - Integrate LLMs and multimodal models with robust serving infrastructure.
- Evaluation & Safety - Design automated and human-in-the-loop evaluation systems.
- Data & Feature Engineering - Own pipelines for training, fine-tuning, retrieval-augmented generation (RAG) and vector search.
- Cross-functional Collaboration - Work closely with product, design and customer success.
Requirements
- 3+ years working with production ML/AI systems, ideally with agentic or multi-agent architectures.
- Practical experience integrating LLMs and multimodal models (API-based or self-hosted) into applications.
- Strong software engineering skills (Python, TypeScript or similar) with production-grade system design and testing.
- Experience with retrieval systems, vector databases and feature stores preferred.
- Track record of shipping end-to-end systems: data, models, infrastructure and monitoring.
- Bias, safety and evaluation mindset — able to design metrics and mitigation strategies for real-world deployments.
- Collaborative, high-ownership approach and clear communication with cross-functional partners.
Skills & Technologies
Benefits & Perks
Recruitment Process
- 1Recruiter screening
- 2Technical task
- 3Code Interview
- 4Trial with us in the office

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