26.10.2026 aktualisiert
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Senior Data/AI Consultant & Systems Architect
Södertälje, Schweden
Weltweit
MSc. Artificial Intelligence in Computer ScienceÜber mich
Senior data and AI engineer and systems architect with over 10 years across enterprise, biotech, automotive and public sector. Databricks, Snowflake, BigQuery, dbt, Terraform. LLMs, RAG, agentic workflows, GPU fine-tuning. Stockholm. Open to consulting, contract and permanent roles.
Skills
APIsKünstliche IntelligenzBusiness Intelligence DevelopmentClient-Server-ArchitekturCloud-EngineeringData ArchitectureDateninfrastrukturData TransformationDatensystemeData Transformation ServicesDigitale ArchitekturEnterprise Architecture FrameworkData IntelligenceMachine LearningSoftware Architecture
AI/ML Engineering and LLM Orchestration
Expertise in building and deploying AI/ML systems using PyTorch, TensorFlow/Keras, Hugging Face Transformers, LangChain/LangGraph, LlamaIndex, and frameworks for RAG, fine-tuning, agentic workflows, multi-agent systems, tool calling, and multi-GPU model adaptation including PEFT/LoRA and FSDP2.
Data Engineering and Pipeline Development
Deep experience in ETL/ELT design, batch and streaming pipeline development using PySpark, Databricks, Snowflake, BigQuery, and dbt, with strong focus on data quality, governance, and real-time processing across GCP, AWS, and Azure.
Cloud Infrastructure and MLOps
Proficiency in designing and managing cloud infrastructure on GCP, AWS, and Azure, with hands-on experience in Docker, Kubernetes, Terraform, CI/CD pipelines via GitHub Actions and GitLab, MLflow, Kubeflow, and HPC environments including EuroHPC and Slurm.
Programming and Backend Development
Strong programming background across Python, SQL, PySpark, TypeScript, Node.js, ReactJS, Go, Rust, C/C++, Bash, Java, Scala, PHP, Julia, with frameworks including FastAPI, Flask, Spring Boot, and REST APIs.
Architecture Frameworks and System Design
Application of established architecture frameworks such as C4, V-model, TOGAF, UML, and SystemWeaver to translate complex business requirements into scalable technical architectures.
Standards and Compliance
Solid knowledge of automotive and quality standards including ISO 26262, ASPICE, ISO/SAE 21434, ISO/PAS 8800, ISO/IEC 5259, ISO 13485, ISO 9001, ISO 42001, as well as regulatory frameworks such as EU AI Act, GDPR/SOC2, NIS2, and DORA.
Data Science and Evaluation Methods
Application of CRISP-DM, CRISP-ML(Q), LLM evaluation frameworks, and statistical and quantitative methods to assess model performance and ensure governed, reproducible results.
Security and Networking
Knowledge of OAuth 2.0, OpenID Connect, session and token security, AES-256-GCM encryption, VPNs, SSH, FTP/SFTP, HTTP/HTTPS, SMTP, TLS/SSL, and Nginx.
Reporting, Visualization and Documentation
Experience with Power BI, Looker, SAS, Matplotlib/Seaborn/Plotly, Streamlit, Swagger, MkDocs, Mintlify, Markdown, LaTeX/Overleaf, Confluence, and technical architecture documentation.
Databases and Storage
Hands-on experience with PostgreSQL, MySQL, SQLite, MongoDB, Neo4j (Graph), Vector Databases, and Embeddings Storage for structured and unstructured data management across distributed systems.
Expertise in building and deploying AI/ML systems using PyTorch, TensorFlow/Keras, Hugging Face Transformers, LangChain/LangGraph, LlamaIndex, and frameworks for RAG, fine-tuning, agentic workflows, multi-agent systems, tool calling, and multi-GPU model adaptation including PEFT/LoRA and FSDP2.
Data Engineering and Pipeline Development
Deep experience in ETL/ELT design, batch and streaming pipeline development using PySpark, Databricks, Snowflake, BigQuery, and dbt, with strong focus on data quality, governance, and real-time processing across GCP, AWS, and Azure.
Cloud Infrastructure and MLOps
Proficiency in designing and managing cloud infrastructure on GCP, AWS, and Azure, with hands-on experience in Docker, Kubernetes, Terraform, CI/CD pipelines via GitHub Actions and GitLab, MLflow, Kubeflow, and HPC environments including EuroHPC and Slurm.
Programming and Backend Development
Strong programming background across Python, SQL, PySpark, TypeScript, Node.js, ReactJS, Go, Rust, C/C++, Bash, Java, Scala, PHP, Julia, with frameworks including FastAPI, Flask, Spring Boot, and REST APIs.
Architecture Frameworks and System Design
Application of established architecture frameworks such as C4, V-model, TOGAF, UML, and SystemWeaver to translate complex business requirements into scalable technical architectures.
Standards and Compliance
Solid knowledge of automotive and quality standards including ISO 26262, ASPICE, ISO/SAE 21434, ISO/PAS 8800, ISO/IEC 5259, ISO 13485, ISO 9001, ISO 42001, as well as regulatory frameworks such as EU AI Act, GDPR/SOC2, NIS2, and DORA.
Data Science and Evaluation Methods
Application of CRISP-DM, CRISP-ML(Q), LLM evaluation frameworks, and statistical and quantitative methods to assess model performance and ensure governed, reproducible results.
Security and Networking
Knowledge of OAuth 2.0, OpenID Connect, session and token security, AES-256-GCM encryption, VPNs, SSH, FTP/SFTP, HTTP/HTTPS, SMTP, TLS/SSL, and Nginx.
Reporting, Visualization and Documentation
Experience with Power BI, Looker, SAS, Matplotlib/Seaborn/Plotly, Streamlit, Swagger, MkDocs, Mintlify, Markdown, LaTeX/Overleaf, Confluence, and technical architecture documentation.
Databases and Storage
Hands-on experience with PostgreSQL, MySQL, SQLite, MongoDB, Neo4j (Graph), Vector Databases, and Embeddings Storage for structured and unstructured data management across distributed systems.
Erfahrung
Berufserfahrungmehr als 10 Jahre
Freelancer seit2015
Sprachen
Englishverhandlungssicher
Projekthistorie
Lead data architecture and AI strategy engagements for enterprise clients. Design end-to-end data pipelines and GenAI solutions on GCP and AWS, from data readiness assessment through architecture to delivery. Collaborate directly with client stakeholders and translate business requirements into data engineering and architectural solutions. Advise on data modeling, pipeline design, and cloud platform selection.
Conformly AI develops tools for AI-powered compliance analysis in automotive safety engineering, supporting standards including ISO 26262, ASPICE, and ISO/SAE 21434. Designed and built the compliance-analysis backend end to end including document ingestion, retrieval, and an LLM evaluation engine. Diagnosed and fixed a production defect reducing unparseable evaluator responses from 32% to 3.6%. Established the evaluation and governance framework including pre-registered experiment cards, Inspect AI harness, bootstrap confidence intervals, and data governance per EU AI Act and ISO/PAS 8800. Built the model-adaptation programme with a 4,615-document synthetic corpus and a 90-run LoRA grid on Axolotl. Secured and delivered a EuroHPC allocation on MareNostrum 5 (100,000 CPU-hours).
Designed and developed software and data systems, and modeled databases and computational systems. Engineered data systems, applied ML techniques, and developed GenAI solutions. Built and maintained Databricks and Snowflake pipelines in PySpark, including streaming and real-time processing on Databricks and GCP. Designed, implemented, and managed infrastructure across GCP, AWS, and Azure.