Tkxel
AI Lead / AI Architect
Tkxel is hiring an AI Lead / AI Architect in Lahore to provide technical leadership for enterprise AI initiatives — defining AI/ML architecture and strategy, designing end-to-end solutions spanning traditional ML, Generative AI/LLMs, RAG, and AI agents, and guiding teams through MLOps productionization on Kubernetes and cloud.
- Compensation
- Not disclosed
- Location
- Lahore, Pakistan
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Architecture
- Posted
Skills
Must have
- Minimum 7 years of experience in AI/ML, data science, software engineering, or related fields
- Strong hands-on experience designing and delivering enterprise AI/ML solutions
Full description
AI Lead / AI ArchitectAI Lead / AI Architect with a minimum of 7 years of experience in AI/ML, data science, software engineering, or related fields, including strong hands-on experience designing and delivering enterprise AI/ML solutions. Will provide technical leadership for AI initiatives, define AI architecture and solution patterns, and guide AI/ML solutions from business requirements through production deployment.
Key Responsibilities
- Define the AI/ML architecture and technical strategy for enterprise AI initiatives.
- Translate business objectives and use cases into scalable, secure, and production-ready AI solutions.
- Lead the design of end-to-end AI architectures, including models, data, APIs, applications, infrastructure, and integration components.
- Evaluate AI/ML technologies, frameworks, platforms, and models and recommend the most appropriate solutions.
- Establish reusable AI architecture patterns, standards, and best practices.
- Define technical approaches for traditional ML, Generative AI, LLMs, RAG, and AI Agents.
- Work closely with Business Analysts and Product teams to assess AI use cases, technical feasibility, value, data requirements, and dependencies.
- Guide Data Scientists and AI/ML Engineers in model development, experimentation, evaluation, and productionization.
- Work with Data Engineers to define data architecture and pipelines required for AI/ML solutions.
- Work with Backend and Frontend teams to integrate AI capabilities into enterprise applications.
- Work with DevOps/MLOps teams to establish production deployment architectures across on-premises Kubernetes and cloud environments.
- Define requirements for model serving, inference, scalability, monitoring, and lifecycle management.
- Establish appropriate approaches for model versioning, deployment, monitoring, retraining, and rollback.
- Ensure AI solutions meet requirements for security, performance, scalability, availability, and maintainability.
- Identify technical risks, architectural constraints, dependencies, and technology gaps.
- Lead technical design reviews and provide guidance on complex AI/ML architecture decisions.
- Ensure AI solutions are aligned with enterprise architecture and security standards.
- Provide technical leadership and mentorship to AI/ML and engineering teams.
- Stay current with developments in and assess their relevance to the organization.