AI Engineer
Actively Hiring
Full-time $121k Posted 7 days ago
Responsibilities
- check_circle Independently deliver scoped AI, GenAI, NLP, and RAG features of moderate complexity
- check_circle Develop and enhance RAG pipelines, including document parsing and ingestion, chunking and metadata strategies, query transformation, retrieval and ranking, response generation and grounding
- check_circle Build GenAI features using LLM APIs, structured prompting, and orchestration frameworks (e.g., LangChain, LangGraph, DSPy, etc.)
- check_circle Evaluate AI system performance using practical methods such as retrieval metrics, response quality assessment, hallucination analysis, latency measurement, cost analysis, and failure-case testing
- check_circle Understand engineering trade-offs across model quality, latency, cost, reliability, maintainability, and implementation complexity
- check_circle Own features end-to-end – from clarification and experimentation to deployment and initial support
- check_circle Translate requirements into user stories and provide implementation plans, as well as own features end-to-end throughout the software development lifecycle - from clarification and experimentation to deployment and initial support
- check_circle Identify risks, dependencies, and data limitations early and propose workable solutions
- check_circle Challenge unclear requirements and contribute with pragmatic, value-driven alternatives
- check_circle Stay close to new developments in LLMs, RAG, prompt optimization, model evaluation, fine-tuning, and applied AI frameworks, and assess where they create real business impact
- check_circle A degree in Computer Science, Software Engineering, AI, Machine Learning, or similar- or equivalent professional experience
- check_circle 3+ years of professional AI engineering/applied data science experience, including hands-on experience with AI, NLP, machine learning, deep learning, or language-model-based applications
- check_circle Strong Python skills and experience building clean, maintainable, and production-ready software
- check_circle Hands-on experience with GenAI or LLM-based solutions or open-source models
- check_circle Solid understanding of software engineering practices (testing, CI/CD, version control, etc.)
- check_circle Experience with model evaluation, monitoring, or experiment tracking tools (i.e., MLflow or similar).
- check_circle Ability to work in cross-functional, agile teams and communicate clearly in English
Preferred qualifications
- Experience with cloud platforms such as Google Cloud or similar
- Familiarity with RAG architectures, embeddings, vector databases, and retrieval techniques
- Exposure to fine-tuning or model optimization approaches
- Experience with Kedro for building modular, reproducible data and ML pipelines, and KServe for scalable, production-grade model deployment and inference on Kubernetes
- Knowledge of agentic workflows, tool-calling systems, agentic search, MCP, or A2A integration patterns
Benefits
- check_circle Employment based on an employment contract, along with a comprehensive benefits package
- check_circle Training and development programs, as well as access to an e-learning platform
- check_circle Onboarding program with the support of a dedicated Buddy
- check_circle Participation in an annual, company-wide integration event
- check_circle A work environment based on Scandinavian organizational culture
- check_circle Opportunities for growth through our internal program
Tags & Focus Areas
Fulltime Ai Ai Engineer
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