Head of Research & Development

Our client an AI-powered technology company focused on building and deploying intelligent systems that help enterprises and public sector institutions modernize operations improve decision-making and scale efficiently is looking to add a Head of Research and Development to lead their AI innovation efforts guiding applied research and translating it into scalable production-ready solutions. This role balances technical leadership with execution ensuring research initiatives are aligned with business priorities and deliver tangible value.

The company combines applied research advanced analytics and software engineering to deliver AI-driven platforms across sectors such as finance healthcare and government. Its focus is on translating emerging technologies into practical production-ready solutions that deliver measurable impact.

Core Responsibilities

• Monitor global AI and technology trends identifying opportunities relevant to Xobriqs markets
• Define and drive R&D priorities in alignment with company strategy
• Lead the development of reusable AI platforms frameworks and models
• Oversee rapid prototyping testing and validation of new AI solutions
• Partner closely with product and engineering teams to transition research into production
• Build mentor and manage a high-performing R&D team
• Contribute to thought leadership through publications presentations or industry engagement where relevant

Required Qualifications & Experience

• 7 years of experience in machine learning AI data science or related fields with at least 3 years in a technical leadership role
• Proven track record of translating research or advanced concepts into deployed real-world systems
• Strong working knowledge of modern AI approaches including large language models (LLMs) agent-based systems and/or multimodal AI
• Experience working cross-functionally with engineering and product teams to deliver scalable solutions

Education

• Masters or PhD in Computer Science Machine Learning or a related field

Additional Experience & Evaluation Criteria

• Demonstrated research capability through one or more of the following:
• Published or co-authored research papers (academic or industry)
• Contributions to open-source AI/ML projects
• Patents technical white papers or significant internal research initiatives
• Graduate-level thesis or dissertation in a relevant field
• Ability to clearly communicate complex technical concepts including:
• Explaining prior research or projects and their real-world application Articulating trade-offs between different AI approaches
• Experience managing R&D budgets timelines and teams in a scaling or high-growth environment is an added advantage