Posted:2 weeks ago|
Platform:
Work from Office
Full Time
Job Summary
The Senior Scientist Responsible AI & Research Integration is a hybrid role embedded across the Responsible AI Office and the AI Research Lab. This role is focused on advancing the frontiers of Responsible AI and AI safety while ensuring that research outcomes directly inform the companys products platforms and internal practices.
This role is approximately 60% focused on research pursuing foundational and applied investigations into agentic safety oversight mechanisms system interoperabi
Responsibilities
Lead and contribute to applied research efforts in Responsible AI including topics such as model alignment transparency behavioral safety agentic behavior and oversight mechanisms for autonomous or multi-agent systems
Collaborate with the AI Research Lab and Responsible AI Office to define meaningful research agendas that support both long-term inquiry and practical application
Translate research findings into components evaluation methods or controls that can be incorporated into product features platform architecture or internal governance frameworks
Participate in the design and validation of tools that address emerging safety risks and implementation gaps in AI development and deployment
Product Strategy & Market Intelligence (25%)
Develop product roadmap specifications by translating emerging research and market needs into concrete technical requirements
Conduct technical due diligence and evaluation of early-stage startups in the AI safety governance and trust space
Assess commercial viability and enterprise adoption potential of safety and governance solutions
Monitor competitive landscape and identify market gaps in responsible AI tooling
Act as a key connector between research and engineering teams working closely with product leads and framework architects to ensure feasibility and alignment between scientific exploration and development priorities
Ecosystem Development & Partnerships (15%)
Build and manage collaborative relationships with academic labs research consortia and external fellows identifying opportunities for co-authored research joint development of tools or benchmarks and knowledge exchange
Establish and maintain relationships with leading AI safety research groups globally (Stanford HAI UC Berkeley CHAI MIT CSAIL Oxford etc.)
Scout and evaluate emerging companies developing solutions for AI oversight interpretability alignment and governance
Build relationships with AI safety startups and scale-ups to identify partnership investment or acquisition opportunities
Participate in venture capital networks and startup accelerators focused on AI safety technologies
External Representation & Thought Leadership
Coordinate and contribute to external working groups focused on advancing standards best practices or evaluation methodologies for Responsible AI and safety-aligned systems
Represent the company in research summits public forums and academic communities to share work shape dialogue and help position the organization as a trusted leader in the development of responsible high-performing AI systems
Contribute to internal education and knowledge dissemination efforts by sharing research findings facilitating workshops and advising teams on complex or emergent risks in AI systems
Required Qualifications
This role requires a strong background in AI/ML research with a focus on safety Responsible AI Trust agentic research and related technical domains. Candidates should have experience contributing to original research working across interdisciplinary teams engaging external research ecosystems and been involved in product launches.
Technical Requirements
PhD in Computer Science Artificial Intelligence Cognitive Systems or a related discipline
Strong publication record or equivalent contributions in AI safety agent alignment multi-agent systems fairness interpretability or risk-aware AI
Proven ability to translate research into production-ready tools software components or product capabilities
Hands-on experience conducting applied research and collaborating with engineering or product teams
Familiarity with foundational model architectures ML evaluation pipelines and lifecycle governance frameworks
Experience with agentic AI systems multi-agent coordination and autonomous system oversight
Knowledge of AI governance frameworks regulatory landscapes (EU AI Act emerging US standards) and compliance requirements
Understanding of cybersecurity implications for AI systems especially autonomous agents
Proven track record of evaluating early-stage AI companies and technologies
Experience building strategic partnerships across academia industry and policy organizations
Understanding of venture capital and startup ecosystem dynamics in AI safety space
Network within the responsible AI research and startup communities
Familiarity with enterprise AI risk management and safety infrastructure needs
Strategic & Communication Skills
Comfort working across academic policy and industry environments and engaging with technical audiences at all levels
Ability to synthesize insights from academic research startup innovation and enterprise needs into coherent product strategies
Experience creating technical roadmaps that balance cutting-edge research with practical implementation
Proven ability to represent organizations in high-stakes technical and policy discussions
Skills in scenario planning for rapidly evolving AI governance landscape
Cognizant
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