Responsible AI & Research Integration

10 - 14 years

35 - 65 Lacs

Posted:2 weeks ago| Platform: Naukri logo

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Job Type

Full Time

Job Description



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

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