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 Xobriq's 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

• Master's 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