08/12/2026 updated
100 % available
Lead AI Engineer | Applied AI Consultant
Stockholm, Sweden
Only remote
PhD degreeAbout me
Product-focused Lead AI Engineer and applied AI consultant with 15+ years of experience building data, ML and AI products across fintech, payments, manufacturing, telecom and academia.
Artificial IntelligenceApache AirflowMachine LearningDatadogGoogle CloudFeature EngineeringData SciencePrompt EngineeringGenerative AI
AI Engineering and LLM Application Development
Expertise in building conversational AI, LLM agents and multi-agent workflows using Python, Google ADK, OpenAI API, GPT models, Gemini, Claude, Vertex AI, LiteLLM, agentic AI, RAG, embeddings, FAISS, Chainlit, prompt engineering, structured outputs, tool calling, multimodal LLMs/VLMs, text-to-SQL, Model Context Protocol (MCP), LLM evaluation and workflow evaluation.
Data Science and Machine Learning
Strong background in data science and machine learning including anomaly detection, NLP classification, credit risk modeling, feature engineering, binary classification, statistical analysis and model explainability, using pandas, scikit-learn, XGBoost, Meta Prophet, SHAP and Jupyter.
Product and Backend Development
Hands-on experience with product and backend development using Python, FastAPI, Flask, Pydantic, Docker, GCP Cloud Run, SQLAlchemy, Redis, pytest, unittest and AI-assisted software development, with use of observability tooling including Datadog, Grafana, GitHub Actions and CircleCI.
Data Engineering and Analytics
Proficiency in data engineering and analytics using SQL, BigQuery, Redshift, Amazon Athena, Presto, AWS Glue, PySpark, Apache Airflow, ETL data pipelines and analytics engineering, with familiarity with Cube.js semantic layer and Dask.
Applied AI for Product Development
Experience turning ambiguous business problems into shipped AI product capabilities, including structured document extraction, text-to-SQL analytics, conversational AI and multi-agent workflows across fintech, payments, manufacturing and telecom.
Cloud Platforms and Infrastructure
Practical experience with Google Cloud Platform (Compute Engine, App Engine, BigQuery, Datastore, Firestore), AWS (Athena, Glue, SageMaker), GCP Cloud Run and Docker for scalable AI and data solutions.
NLP and Text Analytics
Development of NLP-based solutions including transaction tagging services, multi-label email classification, credit-default modeling and binary classification using techniques such as XGBoost, BoostARoota, SHAP and scikit-learn.
Engineering Management and Team Leadership
Leadership and management experience including hiring, onboarding and coaching data scientists, owning technical roadmaps and cross-functional delivery for AI, ML and analytics capabilities in B2B customer-facing products.
Expertise in building conversational AI, LLM agents and multi-agent workflows using Python, Google ADK, OpenAI API, GPT models, Gemini, Claude, Vertex AI, LiteLLM, agentic AI, RAG, embeddings, FAISS, Chainlit, prompt engineering, structured outputs, tool calling, multimodal LLMs/VLMs, text-to-SQL, Model Context Protocol (MCP), LLM evaluation and workflow evaluation.
Data Science and Machine Learning
Strong background in data science and machine learning including anomaly detection, NLP classification, credit risk modeling, feature engineering, binary classification, statistical analysis and model explainability, using pandas, scikit-learn, XGBoost, Meta Prophet, SHAP and Jupyter.
Product and Backend Development
Hands-on experience with product and backend development using Python, FastAPI, Flask, Pydantic, Docker, GCP Cloud Run, SQLAlchemy, Redis, pytest, unittest and AI-assisted software development, with use of observability tooling including Datadog, Grafana, GitHub Actions and CircleCI.
Data Engineering and Analytics
Proficiency in data engineering and analytics using SQL, BigQuery, Redshift, Amazon Athena, Presto, AWS Glue, PySpark, Apache Airflow, ETL data pipelines and analytics engineering, with familiarity with Cube.js semantic layer and Dask.
Applied AI for Product Development
Experience turning ambiguous business problems into shipped AI product capabilities, including structured document extraction, text-to-SQL analytics, conversational AI and multi-agent workflows across fintech, payments, manufacturing and telecom.
Cloud Platforms and Infrastructure
Practical experience with Google Cloud Platform (Compute Engine, App Engine, BigQuery, Datastore, Firestore), AWS (Athena, Glue, SageMaker), GCP Cloud Run and Docker for scalable AI and data solutions.
NLP and Text Analytics
Development of NLP-based solutions including transaction tagging services, multi-label email classification, credit-default modeling and binary classification using techniques such as XGBoost, BoostARoota, SHAP and scikit-learn.
Engineering Management and Team Leadership
Leadership and management experience including hiring, onboarding and coaching data scientists, owning technical roadmaps and cross-functional delivery for AI, ML and analytics capabilities in B2B customer-facing products.
Experience
Professional experience10+ years
Freelancer since2026
Languages
EnglishFluent
Project history
Shaped CEO-office needs into concrete AI product workflows for daily briefing and email triage. Built a CEO-facing generative AI Executive Assistant with conversational and multi-agent workflows, delivered from early requirements to active rollout in approximately 6 weeks. Designed and implemented multi-agent workflows for information synthesis, email classification, prioritization, source-grounded summaries and task-relevant executive support. Built a domain-expert evaluation framework for highly tailored multi-label email classification. Achieved strong recall-weighted classification performance with parallel batches of 5 emails processed in under 10 seconds. Implemented applied AI product safeguards including structured outputs, source-linked summaries and human approval flows. Estimated impact: approximately 2.5 hours saved in email reading time per week. Tech: Python, Google ADK, Gemini Enterprise Agent Platform, Claude and Gemini LLMs, Vertex AI, LiteLLM, Pydantic, Gmail, Google Drive, Google Calendar and Slack APIs, MCP, Docker.
Parental leave from October 2025 to January 2026.
Led AI/ML product development in an early-stage US payments startup with leadership, management and hiring responsibility for a team of 2-4. Owned technical roadmap and cross-functional delivery for AI, ML and analytics capabilities in B2B customer-facing payments products. Reported directly to the CPO. Shipped merchant payments monitoring and alerting using anomaly detection. Built a production customer-facing invoice PDF parser using OpenAI Structured Outputs, multimodal GPT-4.1, OCR and PyMuPDF, reducing monthly manual extraction from approximately one FTE day to around 20 minutes (24x reduction). Co-developed a live customer-facing payments analytics AI agent using text-to-SQL, GPT-4o, tool calling, schema grounding and light RAG over company documentation. Tech: Python, OpenAI API, GPT models, Gemini, Claude, agentic AI, generative conversational AI, document AI, PDF extraction, RAG, embeddings, FAISS, Chainlit, prompt engineering, structured outputs, tool calling, multimodal LLMs/VLMs, text-to-SQL, SQL, Redshift, Cube.js, Meta Prophet, ETL, anomaly detection.