Position Summary
The Director of AI Software Solutions is responsible for defining and leading the organization's artificial intelligence software strategy, architecture, solution development, and deployment initiatives. This role drives the successful adoption of AI technologies across products, services, and business operations, ensuring solutions deliver measurable business value while maintaining security, compliance, scalability, and ethical AI standards.
The Director will lead cross-functional teams of software engineers, data scientists, solution architects, product managers, and business stakeholders to design, develop, and operationalize AI-powered solutions. This individual serves as both a strategic leader and a technical expert, bridging business objectives with innovative AI capabilities.
Key Responsibilities
AI Strategy & Leadership
- Develop and execute the company's AI software solutions strategy aligned with business objectives.
- Identify opportunities to leverage AI, machine learning, generative AI, and automation technologies to improve products, services, and operations.
- Establish AI governance, responsible AI practices, and technology roadmaps.
- Evaluate emerging AI technologies, platforms, and industry trends to drive innovation.
Solution Architecture & Delivery
- Lead the design and implementation of scalable AI-enabled software solutions.
- Define enterprise architecture standards, integration strategies, and best practices for AI applications.
- Oversee the full software development lifecycle, from concept through deployment and ongoing optimization.
- Ensure AI solutions meet performance, security, compliance, and reliability requirements.
Product & Business Partnership
- Collaborate with business leaders to identify high-value AI use cases and define solution priorities.
- Translate business requirements into technical strategies and implementation plans.
- Develop business cases, ROI models, and success metrics for AI initiatives.
- Present AI roadmaps and solution outcomes to executive leadership.
Team Leadership & Talent Development
- Build, mentor, and lead high-performing teams of AI engineers, software developers, architects, and technical managers.
- Foster a culture of innovation, collaboration, continuous learning, and operational excellence.
- Establish talent development programs focused on AI, cloud technologies, and modern software engineering practices.
- Drive workforce readiness and AI adoption across the organization.
AI Platform & Technology Management
- Oversee AI development environments, cloud platforms, and MLOps/LLMOps frameworks.
- Establish standards for model lifecycle management, deployment, monitoring, and continuous improvement.
- Ensure efficient use of cloud, data, and AI infrastructure resources.
- Manage relationships with technology vendors and strategic partners.
Governance, Security & Compliance
- Establish AI governance frameworks, risk management processes, and security controls.
- Ensure compliance with regulatory, legal, privacy, and ethical AI requirements.
- Implement model monitoring and validation processes to ensure accuracy and fairness.
- Collaborate with cybersecurity, legal, and compliance teams to minimize operational and reputational risks.
Required Qualifications
Education
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related field.
- Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Business Administration (MBA), or a related discipline preferred.
Experience
- 12+ years of progressive experience in software engineering, enterprise solutions, or technology leadership.
- 5+ years of leadership experience managing software engineering, AI, or data science teams.
- Proven experience delivering enterprise-scale AI, machine learning, or generative AI solutions.
- Experience leading large cross-functional programs involving multiple business and technical stakeholders.
- Demonstrated success in building and scaling high-performance technical teams.
Technical Expertise
- Strong understanding of:
- Artificial Intelligence (AI)
- Machine Learning (ML)
- Generative AI (GenAI)
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Agentic AI Systems
- Natural Language Processing (NLP)
- Computer Vision (preferred)
- Experience with cloud platforms such as:
- Microsoft Azure AI
- Azure OpenAI Service
- AWS AI/ML Services
- Google Cloud Vertex AI
- Knowledge of:
- MLOps and LLMOps practices
- Software architecture and microservices
- API design and integration
- Data engineering and analytics platforms
- DevOps and CI/CD methodologies
- Cybersecurity and enterprise architecture
Leadership Competencies
- Strong executive communication and stakeholder management skills.
- Ability to translate complex technical concepts into business value.
- Strategic thinker with strong problem-solving and decision-making capabilities.
- Proven ability to drive organizational change and digital transformation initiatives.
- Experience managing budgets, vendors, and technology investments.
Preferred Qualifications
- Fluent in English with working experience in US
- AI-related certifications such as:
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Azure Solutions Architect Expert
- AWS Machine Learning Specialty
- Google Professional Machine Learning Engineer
- Experience implementing AI governance and Responsible AI frameworks.
- Background in enterprise software products, SaaS platforms, or digital transformation programs.
- Experience with Copilot, OpenAI, Azure OpenAI, agent-based systems, and enterprise AI adoption strategies.
- Knowledge of industry regulations affecting AI, data privacy, and security.
