Director of Staff Development

Education and work experience

• Experience in the Tech/AI industry: Experience in the position of Head of L&D, T&D Director, or HRD in product IT companies, AI startups, or large technological ecosystems for 3–5 years is required.

• Education: Higher education (IT, management, HR management, psychology). A huge plus will be a technical background or understanding of the specifics of software/AI product development.

• International experience: Desirable experience working with distributed (remote) international teams and knowledge of English at the Upper-Intermediate/Advanced level to work with global benchmarks and providers.

Professional knowledge and skills (Hard Skills)

• Understanding of AI talents: Deep understanding of career tracks, motivation, and burnout of IT specialists (Data Scientists, ML engineers, LLM developers, PMs).

• AI in HR (Tech HR): Experience in implementing AI tools in training, evaluation, and staff adaptation processes (for example, using AI for course personalization, engagement analysis, or onboarding automation).

• Upskilling & Reskilling: Skills in quickly building retraining programs for new technological stacks and tools (for example, generative AI, new frameworks).

• Knowledge Management: Experience in creating a unified knowledge base, peer-to-peer learning systems (developers teaching developers), and facilitating internal tech talks/hackathons.

• Data-driven approach: Ability to work with HR analytics, efficiency metrics (eNPS, Time to Productivity, Retention rate, ROI of training) based on data, not intuition.

Personal and managerial qualities (Soft Skills)

• Agile mindset: Willingness to work in conditions of high uncertainty, flexibility, ability to quickly change focus and development strategies in response to changes in the AI market.

• Developed emotional intelligence (EQ): Ability to find an approach to complex engineering talents ("introverts"), prevent burnout in conditions of high work pace.

• Culture of experimentation: Willingness to test non-standard training formats (gamification, micro-learning in messengers, VR/AR).

Key tasks in Koz AI

• Talent development strategy: Synchronizing training and development plans of employees with the strategic roadmap of Koz AI product development.

• Adaptation (Onboarding): Building a fast and seamless process for bringing IT specialists to full project capacity (reducing Time to Productivity).

• Retention: Developing individual development plans (IDPs) and transparent grades to minimize poaching of employees by international giants.

• Development of AI literacy: Enhancing the qualifications of non-technical teams in the company (marketing, sales, HR) in the use of company products and AI tools.

• Internal employer brand: Building a strong engineering community within the company, organizing internal hackathons, R&D sessions, and knowledge sharing.

Education and work experience

• Experience in the Tech/AI industry: Mandatory experience in the position of Head of L&D, T&D Director, or HRD in product IT companies, AI startups, or large technological ecosystems for 3–5 years.

• Education: Higher education (IT, management, human resources, psychology). A huge plus will be a technical background or understanding of the specifics of software / AI product development.

• International experience: Experience working with distributed (remote) international teams and knowledge of English at the Upper-Intermediate/Advanced level is desirable for working with global benchmarks and providers.

Professional knowledge and skills (Hard Skills)

• Understanding of AI talent specifics: Deep understanding of career tracks, motivation, and burnout of IT specialists (Data Scientists, ML engineers, LLM developers, PMs).

• AI in HR (Tech HR): Experience implementing AI tools in training, evaluation, and employee onboarding processes (e.g., using AI for course personalization, engagement analysis, or onboarding automation).

• Upskilling & Reskilling: Skills in quickly building retraining programs for new technological stacks and tools (e.g., generative AI, new frameworks).

• Knowledge Management: Experience in creating a unified knowledge base, peer-to-peer learning systems (developers teaching developers), and facilitating internal tech talks/hackathons.

• Data-driven approach: Ability to work with HR analytics, performance metrics (eNPS, Time to Productivity, Retention rate, ROI of training) based on data, not intuition.

Personal and managerial qualities (Soft Skills)

• Agile mindset: Willingness to work in conditions of high uncertainty, flexibility, ability to quickly change focus and development strategies in response to market changes in AI.

• Developed emotional intelligence (EQ): Ability to connect with complex engineering talents ("introverts"), prevent burnout in high-paced work environments.

• Culture of experimentation: Willingness to test unconventional training formats (gamification, micro-learning in messengers, VR/AR).

• Talent development strategy: Synchronization of employee training and development plans with the strategic roadmap for Koz AI product development.

• Adaptation (Onboarding): Establishing a fast and seamless transition for IT specialists to reach full project productivity (reducing Time to Productivity).

• Retention: Development of individual development plans (IDPs) and transparent grades to minimize employee poaching by international giants.

• AI Literacy development: Enhancing the skills of non-technical teams within the company (marketing, sales, HR) in the use of company products and AI tools.

• Internal employer branding: Building a strong engineering community within the company, organizing internal hackathons, R&D sessions, and knowledge sharing.

Strong environment: Working in an ambitious team of young professionals whose AI technologies are valued at the country's leadership level.

• Conditions: Official employment in accordance with the Labor Code of the Republic of Kazakhstan.

• Schedule: 5/2, flexible work schedule with the ability to choose the start time of work

• Growth: Opportunity to test any cool HR initiatives and grow with the scaling of AI products.