AI Software Architect - RDT Biometrics and Clinical Evidence

Roche Polska Sp. z o.o. operates in the pharmaceutical, biotechnology, and regulated healthcare technology industry with a focus on drug development, biometrics, and clinical evidence. The Biometrics and Clinical Evidence team works on enhancing clinical trial design, managing high quality clinical, real-world, imaging, and patient-centric data to generate evidence, provide insights, and support regulatory filings.

• 8–12+ years of technology/software/data experience with proven technical leadership and team building.
• 2+ years experience in pharmaceutical, biotechnology, or regulated healthcare technology industry.
• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, AI, Computational Science, Bioinformatics or related discipline; advanced degree preferred.
• Strong knowledge of modern AI engineering: Generative AI, LLMs, RAG, agentic architectures, tool use/function calling, orchestration, prompt engineering, embeddings, vector search, knowledge retrieval, model selection, observability, fine-tuning, multimodal, and high-throughput serving.
• Experience with Python, API development, microservices, cloud architectures, CI/CD, containers, Git, automated testing, infrastructure/platform patterns, identity/access management, DevSecOps, AI FinOps, and cloud-native orchestration (Kubernetes, AWS, GCP).
• Expertise in data pipelines, semantic models, metadata, structured/unstructured data, vector databases, knowledge graphs, interoperability, data quality, lineage, and provenance.
• Understanding of privacy, security, GxP considerations, validation, auditability, traceability, human-in-the-loop, model evaluation, and AI risk management.
• Knowledge of architecture standards, engineering quality, code review, reusable patterns, technical mentoring, hiring, capability development, prioritization, delivery discipline, vendor lock-in mitigation, buy vs build decisions, and AI change management.
• Strong problem framing, product thinking, scientific curiosity, and value orientation.
• Demonstrated leadership with passion for AI trends, executive presence, business acumen, ability to manage ambiguity and complexity, enterprise mindset, and ability to empower teams.

• Build and lead a high-performing Data & AI Engineering team with a strong engineering culture.
• Define capabilities, roles, development pathways, and engineering practices for AI engineering.
• Translate scientific and business problems into scalable AI solutions in partnership with product and data teams.
• Provide technical leadership from exploration through deployment and lifecycle management.
• Establish reusable patterns, components, and reference architectures for generative AI, agentic workflows, and knowledge retrieval.
• Architect scalable data pipelines, vector search indexes, and hybrid retrieval systems for LLM grounding and retrieval-augmented generation.
• Define structured schema metadata formats and function-calling protocols for agent tool invocation.
• Optimize context windows, chunking strategies, and data freshness to support accurate model reasoning.
• Identify and develop team capabilities aligned with strategic goals and mentor team members.
• Monitor and improve team health, sustainability, collaboration, and work environment standards.
• Manage talent composition and plan for future needs across own and related teams.

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