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Roche

Global pharmaceuticals and diagnostics company

AI Software Architect - RDT Biometrics and Clinical Evidence

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeWarsaw, Poland

About the Job

Requirements

  • The role requires 8–12+ years of relevant technology, software, or data experience, including meaningful technical leadership experience and a proven track record of building high-performing teams.
  • The role requires 2+ years of experience in the pharmaceutical, biotechnology, or regulated healthcare technology industry.
  • A Bachelor's or Master's degree is required in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Computational Science, Bioinformatics, or a related quantitative discipline.
  • Strong practical understanding of modern AI engineering, including generative AI and large language models, retrieval-augmented generation, agentic architectures, tool use and function calling, orchestration, evaluation, prompt and context engineering, embeddings and vector search, knowledge retrieval, model selection, observability, fine-tuning and distillation, multimodal AI, and high-throughput serving such as vLLM.
  • Experience with Python, APIs, microservices, cloud architectures, continuous integration and delivery, containers, Git, automated testing, infrastructure and platform patterns, identity and access management, observability, DevSecOps, AI FinOps including token and GPU cost management, model fallback routing, and cloud-native container orchestration such as Kubernetes and AWS or GCP serverless platforms.
  • Experience with data pipelines, semantic models, metadata, structured and unstructured data, vector databases, knowledge graphs, interoperability, data quality, lineage, and provenance.
  • Knowledge of privacy, security, GxP considerations, validation, auditability, traceability, human-in-the-loop practices, 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-versus-build frameworks, and AI change management.
  • Problem framing and product thinking are required.
  • The role requires scientific curiosity and value orientation.
  • Demonstrated experience building high-performing teams is required.
  • The candidate should have a keen focus on the IT market and major AI trends.
  • The candidate should demonstrate executive presence, business acumen, the ability to navigate ambiguity, and the ability to manage complexity.
  • The candidate must manage risks progressively and in a way that leads to opportunity.
  • The candidate should have an enterprise mindset, break down silos, focus on collaborative delivery, and bring people together across organizational boundaries.
  • The candidate should be able to empower teams and individuals to act autonomously and hold them accountable.
  • The candidate should demonstrate intellectual curiosity, integrity, and a strong interest in innovation.

Responsibilities

  • Build, develop, and lead a high-performing Data and AI Engineering team, establishing an engineering culture focused on technical excellence, experimentation, reuse, collaboration, and measurable impact.
  • Define the capabilities, roles, development pathways, and engineering practices required for AI Engineering across Biometrics and Clinical Evidence and the broader R&D RDT organization.
  • Partner with Product Managers, data teams, and Pharma Development stakeholders to translate high-value business and scientific problems into technically robust AI solutions.
  • Provide technical leadership from early exploration and proof of concept through architecture, development, deployment, adoption, and lifecycle management.
  • Ensure rapid experimentation transitions effectively into production-grade solutions when value is demonstrated.
  • Define and implement reusable patterns, components, and reference architectures for generative AI, retrieval-augmented generation, agentic workflows, knowledge retrieval, and AI-enabled applications.
  • Promote a build-once, reuse-many engineering approach to reduce duplication and accelerate delivery across use cases.
  • Identify capabilities shared across solutions and partner with platform teams to industrialize them as shared services where appropriate.
  • Architect scalable data pipelines, high-throughput vector search indexes, and hybrid retrieval systems tuned for large language model grounding and retrieval-augmented generation.
  • Define and implement structured schema metadata formats and function-calling protocols for precise and reliable agent tool invocation.
  • Optimize dynamic context windows, chunking strategies, and data freshness to improve accurate model reasoning across enterprise domains.
  • Identify and develop future-focused engineering team capabilities aligned with long-term strategic goals.
  • Mentor team members on long-term career paths and create opportunities and roles that support their growth.
  • Address complex systemic roadblocks affecting multiple development teams and coach other managers on effective performance management.
  • Oversee technical and soft-skill development to maintain a balanced, high-performing talent portfolio.
  • Establish and monitor team health and sustainability metrics across several development teams and implement strategies that support long-term balance.
  • Design and implement initiatives to improve collaboration and psychological safety across multiple related development teams or a product area.
  • Identify and resolve systemic impediments affecting multiple development teams to improve the work environment.
  • Manage talent composition for own and related teams, plan for future needs, and maintain a healthy pipeline of skills.

Desired Qualifications

  • An advanced degree is preferred but is not required when equivalent experience demonstrates deep technical capability.

About the Company

Roche

Global pharmaceuticals and diagnostics company

Roche is a global leader in pharmaceuticals and diagnostics. It develops medicines and diagnostic tools that help detect, monitor, and treat diseases, using research and biotechnology to drive new therapies and tests. Roche combines drug development with in-house diagnostic products to support personalized medicine, where treatments are tailored to individual patients based on test results. Its approach differs from many peers by integrating drug discovery with diagnostic capabilities and by expanding its research through strategic acquisitions (like Genentech) to strengthen its biotechnology and R&D capabilities. The company’s goal is to improve patient outcomes and healthcare worldwide by delivering reliable medicines, accurate diagnostic tests, and data-driven care.

Company size
1-10
Company stage
IPO
Headquarters
Basel, Switzerland
Founded
1896

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