10.07.2026 aktualisiert

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AI & Data Leader | Hands-on GenAI, NLP, ML, RAG, Agents and Platforms | Fractional CTO / Head of AI

Berlin, Deutschland
Weltweit
PhD Computer Science with focus on ML/NLP
Berlin, Deutschland
Weltweit
PhD Computer Science with focus on ML/NLP

Profilanlagen

Jurica_Seva_CV_AI_Engineer_Hands_On.pdf
Jurica_Seva_CV_Fractional_CTO_Head_of_AI.pdf
Jurica_Seva_CV_Data_Transformation_Lead.pdf

Über mich

I am a curious builder who enjoys turning complex ideas into useful products. I value open communication, pragmatic decisions and working with people who care about quality. I am especially motivated by ambitious projects where I can combine hands-on work, leadership and long-term thinking.

Skills

ObservabilityAI AgentsGitHub ActionsMLOpsGCPLangChainUnternehmensberatungKlinische EntscheidungshilfeData ArchitectureInformationsextraktionPythonMachine LearningNatural Language ProcessingNoSQLTensorFlowAzure Machine LearningSQLSpracherkennungData SciencePyTorchReact.jsFast Healthcare Interoperability ResourcesLarge Language ModelsGenerative AIDatenstrategieFastAPITeam ManagementReact NativeSpacyTerraformDocker
I’m a hands-on AI and data leader with 10+ years of experience building production AI, ML, NLP, GenAI and data platforms across healthcare, financial services and enterprise software. I have built and led products across the full lifecycle, from research and model development to architecture, validation, deployment and adoption. My work spans healthcare, diagnostics, radiology, financial and regulatory data, enterprise automation and AI tooling, enabling me to transfer patterns across industries and adapt them to different product, data and operating contexts.

What I bring
  1. End-to-end ownership, from ambiguous business problems and technical strategy to architecture, implementation, evaluation and production deployment
  2. Hands-on expertise in LLMs, RAG, AI agents, agentic workflows, NLP, semantic search, knowledge graphs, speech recognition and machine learning
  3. Experience building and leading multidisciplinary AI and data teams, including hiring, mentoring, roadmaps and delivery processes
  4. Strong background in software engineering, cloud-native architecture, APIs, data platforms, MLOps, observability and regulated AI systems
  5. A PhD in Computer Science, Fulbright research experience and an academic background in information retrieval, NLP and semantic technologies
Selected experience
  1. Adia Health: As VP of AI and Data Science, built and led an eight-person multidisciplinary team and owned the development of a healthcare AI and data platform spanning clinical decision support, NLP, knowledge graphs, semantic search, interoperability and cloud infrastructure.
  2. Ada Health: Built clinical NLP, information-extraction and active-learning systems supporting a patient-facing medical reasoning platform.
  3. CompuGroup Medical: Developed disease-prediction models combining EHR data with a medical knowledge graph and helped take a multilingual speech-recognition platform from PoC to MVP.
  4. SYNLAB and Flow Health: Developed and led AI applications for laboratory diagnostics, real-world health data and regulated clinical workflows.
  5. Current fractional work: Designing agentic AI systems, GenAI workflows, document-intelligence pipelines, evaluation frameworks and production architectures across healthcare, financial and regulatory data.
Across these roles, I have helped organisations define AI strategy, establish engineering and evaluation practices, build teams and turn early prototypes into reliable production capabilities.

How I work

I combine hands-on technical depth with product thinking, business judgment and leadership. I value clarity, open communication, pragmatic decisions and high-quality execution. I am most useful where organisations need someone who can understand the complete system and move an initiative from idea to reliable production capability.

I am available for fractional leadership, AI and data strategy, technical architecture, agentic workflow development, hands-on delivery, team building and AI transformation projects.

Sprachen

DeutschverhandlungssicherEnglischverhandlungssicherKroatischMuttersprache

Projekthistorie

Fractional AI / GenAI / Data Transformation Lead

Adriatic Technology Consulting

Banken und Finanzdienstleistungen

10-50 Mitarbeiter

Leading the design and delivery of AI-enabled platforms for private-market valuation, financial-data workflows and internal engineering operations, combining public regulatory filings with proprietary datasets.

Key contributions:
  1. Designed and developed an agentic platform for financial research, extraction, validation and workflow orchestration.
  2. Built AI-assisted pipelines for processing SEC filings and other structured and unstructured financial documents.
  3. Owned the platform architecture across data ingestion, LLM orchestration, search, knowledge graphs, evaluation and production workflows.
  4. Currently redesigning the platform UX to make research, review and correction workflows faster and easier to use.
  5. Collaborate with an annotation and data-operations team in India to improve aggregation, labelling, validation and correction processes.
  6. Developed an Azure-based observability platform for monitoring applications, workflows and operational metrics across the engineering environment.
  7. Introduced AI-assisted tooling and process improvements to reduce manual effort, accelerate review cycles and improve data quality.
  8. Advise leadership on AI strategy, architecture, platform evolution and implementation priorities.
Tech stack: PHP, PrimeVue, Python, AWS, Amazon Bedrock, Azure, PostgreSQL, MongoDB, Amazon Neptune, OpenSearch, SQL, LLMs, AI agents, document intelligence, knowledge graphs, workflow orchestration, observability

Fractional AI / GenAI Lead

Mediaire

Pharma und Medizintechnik

10-50 Mitarbeiter

Leading AI initiatives in radiology and healthcare, translating clinical and product requirements into reliable production systems.

Key contributions:
  1. Designed GenAI, speech-recognition and workflow-automation architectures for regulated clinical use.
  2. Led work on model evaluation, reliability, integration and production deployment.
  3. Improved transcription and clinical-documentation workflows using ASR, VAD and domain-specific processing.
  4. Advised leadership on roadmap priorities, technical trade-offs and AI adoption.
  5. Worked across product, engineering and clinical stakeholders to move prototypes toward production.
Tech stack: Python, GenAI, ASR, VAD, clinical NLP, evaluation, workflow automation, cloud architecture

Head of AI Engineering / Principal AI Engineer

Space Inch

Internet und Informationstechnologie

50-250 Mitarbeiter

Full-time employment. Led AI strategy and hands-on delivery for internal capabilities and client-facing GenAI products.

Key contributions:
  1. Defined AI architecture, tooling, evaluation and deployment practices.
  2. Supported the development of GenAI-enabled product features from requirements through implementation.
  3. Worked across backend services, AI orchestration, data retrieval, infrastructure and frontend integration.
  4. Helped develop the internal AI team and drive broader adoption of AI-first engineering workflows.
  5. Advised clients and delivery teams on feasibility, architecture and production quality.
Reason for leaving:
Chose to leave after concluding that the leadership environment, working style and expectations around autonomy were not the right long-term fit.

Tech stack: Python, LLMs, RAG, AI agents, APIs, React, Next.js, cloud infrastructure, evaluation

Fractional AI Hiring and Organisation Advisor

team.blue

Internet und Informationstechnologie

1000-5000 Mitarbeiter

Supported HR and technology leadership in building and strengthening the company’s AI function. Combined technical AI expertise with organisational design and structured candidate assessment to help define the roles, competencies and team structure required for an effective AI organisation.

Key contributions:
  1. Defined the scope, responsibilities and technical requirements for AI and machine-learning roles.
  2. Reviewed candidate profiles and assessed their technical and organisational fit.
  3. Designed and conducted structured technical interviews for senior AI candidates.
  4. Advised HR and leadership on candidate selection, hiring criteria and team composition.
  5. Helped align recruitment decisions with the company’s broader AI strategy and capability-building goals.
Skills: AI Strategy, Technical Recruiting, AI Organisation Design, Interview Design, Candidate Evaluation, Team Building, Machine Learning, Generative AI, NLP

Head of Data Science, later VP of AI and Data Science

Flow Health / Adia Health

Pharma und Medizintechnik

10-50 Mitarbeiter

Led the strategy, team and technical development of AI-driven healthcare products spanning clinical decision support, healthcare payments, NLP, knowledge graphs, agentic workflows and enterprise data infrastructure.

Key contributions:
  1. Built and led an eight-person multidisciplinary AI and data team across data science, ML engineering and clinical expertise.
  2. Owned the AI and data roadmap, architecture and delivery model, moving initiatives from discovery and proof of concept through validation, integration and production.
  3. Designed agentic AI workflows connecting models, tools, data sources and business processes, including MCP and A2A interoperability.
  4. Led clinical NLP, semantic search and knowledge-graph capabilities across structured and unstructured healthcare data.
  5. Established scalable AWS-based data and AI infrastructure for experimentation, evaluation, observability and production delivery.
  6. Worked across clinical decision support, healthcare payments and interoperability using FHIR, HL7, UMLS, ICD-10, LOINC, SNOMED and CPT.
  7. Defined engineering, governance and evaluation practices aligned with HIPAA, GDPR and SOC 2.
  8. Recruited and mentored the team while advising executives on product, architecture and investment priorities.

Tech stack: Python, AWS, Redshift, Neptune, OpenSearch, Kafka, NLP, GenAI, AI agents, RAG, FHIR, HL7, MLOps, Docker, Terraform, observability

Senior AI Engineer

Synlab

Pharma und Medizintechnik

1000-5000 Mitarbeiter

Developed production-oriented AI and data solutions for laboratory diagnostics, a domain where reliable diagnostic information directly supports clinical decision-making.

Key contributions:

• Designed and implemented ML solutions for laboratory workflow automation, diagnostic support and structured analysis of clinical and operational data.
• Built scalable data and ML pipelines using Python, Databricks, Spark, dbt, dbx and MLflow.
• Worked across data preparation, feature engineering, model development, evaluation, experiment tracking and deployment.
• Collaborated with domain experts and engineering stakeholders to translate laboratory processes into reliable technical solutions.

Tech stack: Python, scikit-learn, TensorFlow, SQL, Databricks, Spark, dbt, dbx, MLflow

Head of Data Science

Lakatu

Medien und Verlage

< 10 Mitarbeiter

Led the design and delivery of applied AI, NLP and information-retrieval solutions for market research and other document-intensive business domains.

Key contributions:
• Led data-science projects from problem definition and solution design through prototyping, evaluation and delivery.
• Built NLP and information-retrieval pipelines for extracting, structuring and analysing insights from large collections of unstructured documents.
• Advised clients and internal stakeholders on AI feasibility, technical architecture, modelling approaches and delivery priorities.
• Established practical development and quality processes while providing technical leadership and hands-on implementation.

Tech stack: Python, NLP, information retrieval, machine learning, semantic search, document processing

Senior AI Specialist/ML Engineer

CompuGroup Medical SE & Co. KGaA

Pharma und Medizintechnik

1000-5000 Mitarbeiter

Developed multilingual, data-centric AI solutions for healthcare software, combining speech recognition, NLP, medical knowledge graphs and machine learning. CGM develops software supporting healthcare professionals and connected clinical processes across the patient journey.

Key contributions:
• Took a multilingual automatic speech-recognition platform for dental care from proof of concept to a containerised MVP deployed on Azure.
• Built disease-prediction models combining MIMIC-III electronic health-record data with a UMLS-based medical knowledge graph.
• Developed pipelines for clinical speech, structured medical concepts and semantic data integration.
• Worked across model development, evaluation, architecture, deployment and communication with product and clinical stakeholders.

Tech stack: Python, PyTorch, Hugging Face, ASR, NLP, Neo4j, UMLS, MIMIC-III, Docker, Azure

Head of NLP

Ada Health

Pharma und Medizintechnik

250-500 Mitarbeiter

Led Ada’s NLP strategy, roadmap and delivery, supporting an intelligent health platform designed to improve health outcomes and clinical excellence.

Key contributions:
• Defined and executed the company-wide NLP vision and roadmap in alignment with product, medical and engineering priorities.
• Led the development of NLP capabilities supporting medical knowledge curation and the clinical reasoning platform.
• Coordinated cross-functional delivery across NLP, medical experts, product and engineering teams.
• Established model-development, annotation, evaluation and knowledge-integration practices.
• Mentored team members and supported hiring, technical planning and stakeholder communication.

Tech stack: Python, TensorFlow, Keras, NLP, information extraction, UMLS, PostgreSQL, GCP, Kubernetes, Helm

NLP Engineer

Ada Health
Built clinical NLP and knowledge-extraction systems supporting Ada’s medical knowledge base and patient-facing reasoning platform.

Key contributions:

• Developed named-entity recognition, concept normalisation, relation extraction and text-classification pipelines for scientific literature and electronic health records.
• Designed pipelines for automatically mapping extracted medical information to UMLS concepts and populating the clinical knowledge base.
• Designed annotation guidelines and coordinated annotation work with medical experts.
• Co-developed an annotation platform with active-learning workflows, reducing manual labelling effort by approximately 30%.
• Built NLP pipelines for medical knowledge curation, question-answering use cases and analysis of user feedback.
• Mentored two junior colleagues and supported cross-functional product delivery.

Tech stack: Python, TensorFlow, Keras, NLP, active learning, UMLS, PostgreSQL, GCP, Kubernetes

Postdoctoral Researcher

Humboldt Universität zu Berlin, Knowledge Management in Bioinformatics

Sonstiges

10-50 Mitarbeiter

Led the technical development of VIST, a precision-oncology search engine built in collaboration with Charité to help researchers and clinicians find and assess clinically relevant cancer-variant information across biomedical literature and oncology knowledge sources.

Key contributions:

• Designed and built the search and information-retrieval platform end to end, from data ingestion and indexing to ranking, search interfaces and evaluation.
• Integrated heterogeneous precision-oncology sources covering genes, variants, diseases, treatments and clinical evidence.
• Applied NLP, entity linking, semantic search and knowledge-based methods to connect biomedical literature with structured oncology information.
• Worked directly with clinical and research collaborators at Charité to translate oncology information needs into product and search requirements.
• Conducted comparative research on public precision-oncology knowledge bases and contributed peer-reviewed publications and evaluation work.

Tech stack: Python, MLTK, Keras, Tensorflow, scikit-learn, Lucene, information retrieval, NLP, semantic search, entity linking, biomedical knowledge bases, oncology data, search systems

Research Developer

University of Sheffield, ACRC

Sonstiges

500-1000 Mitarbeiter

Conducted applied NLP and research-software development within an interdisciplinary research environment.

Key contributions:
  1. Designed and implemented research prototypes and reusable NLP pipelines.
  2. Worked on multilingual text mining, information extraction, semantic technologies and domain-specific knowledge extraction.
  3. Translated research questions into functioning software, datasets and experimental workflows.
  4. Supported model evaluation, technical documentation and collaboration between researchers and software-development stakeholders.
Use more specific project details here where you remember them. The public search did not surface a reliable source describing your exact ACRC project, so I would avoid inventing details.

Academic Research and Teaching in CS, AI, NLP and Information Retrieval

Universities: Zagreb, Purdue

Sonstiges

500-1000 Mitarbeiter

University of Zagreb, Purdue University
Conducted academic research and software development in NLP, information retrieval, semantic search, multilingual text mining and domain-specific knowledge extraction, including biomedical and precision-oncology applications.

Roles included:
  1. Higher Teaching Assistant, Faculty of Organization and Informatics, 08/2014 - 07/2015
  2. Fulbright Visiting Scholar, Purdue University, 08/2009 - 01/2011
  3. Teaching and Research Assistant, University of Zagreb, 11/2006 - 06/2014
Developed research prototypes, NLP pipelines, semantic-search systems, datasets and evaluation frameworks; published peer-reviewed research; collaborated in international and interdisciplinary teams; and taught and supervised computer-science students.

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