we are looking for a AI Architect.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.
Responsibilities:
1. AI Architecture & Technical Leadership
Guide AI architectural direction across Navinas platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure Navinas AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.
Requirements:
Proven experience designing and building complex AI systems that have been successfully delivered to production, with an end-to-end understanding of research, architecture, validation, and production handoff.
Strong hands-on experience with modern AI approaches, including Machine Learning, Deep Learning, and LLM-based systems; experience with agentic AI systems or orchestration patterns is a strong advantage.
Demonstrated ability to move quickly from idea to working prototype, with a strong passion for hands-on experimentation and applied innovation.
Experience working in environments involving sensitive data and regulatory constraints, with an understanding of how these considerations shape AI system design.
Excellent system-level technical judgment, including the ability to identify risks, tradeoffs, and unintended consequences in AI systems.
Proven ability to act as a technical leader without formal authority, influencing and guiding senior peers through collaboration and expertise.
Strong communication and interpersonal skills, with the ability to explain complex technical concepts to diverse stakeholders.
Ability to contribute to clear technical and AI-related compliance documentation.
High proficiency in Python and modern AI/ML tooling.
Optional / Nice-to-Have :
Deep experience in NLP, NLU, or clinical text processing.
Experience deploying LLMs or agent-based systems in production.
Familiarity with cloud-native ML stacks (AWS, Docker, Kubernetes).
Proven experience designing and building complex AI systems that have been successfully delivered to production, with an end-to-end understanding of research, architecture, validation, and production handoff.
Strong hands-on experience with modern AI approaches, including Machine Learning, Deep Learning, and LLM-based systems; experience with agentic AI systems or orchestration patterns is a strong advantage.
Demonstrated ability to move quickly from idea to working prototype, with a strong passion for hands-on experimentation and applied innovation.
Experience working in environments involving sensitive data and regulatory constraints, with an understanding of how these considerations shape AI system design.
Excellent system-level technical judgment, including the ability to identify risks, tradeoffs, and unintended consequences in AI systems.
Proven ability to act as a technical leader without formal authority, influencing and guiding senior peers through collaboration and expertise.
Strong communication and interpersonal skills, with the ability to explain complex technical concepts to diverse stakeholders.
Ability to contribute to clear technical and AI-related compliance documentation.
High proficiency in Python and modern AI/ML tooling.
Optional / Nice-to-Have :
Deep experience in NLP, NLU, or clinical text processing.
Experience deploying LLMs or agent-based systems in production.
Familiarity with cloud-native ML stacks (AWS, Docker, Kubernetes).
This position is open to all candidates.
