Technical Lead - AI
Skills
About This Role
Responsibilities
- Guide the architecture and implementation of AI chatbot solutions leveraging Generative AI, Agentic AI, LangGraph, and Model Context Protocol frameworks.
- Mentor and develop GenAI engineers, fostering a culture of technical excellence and continuous learning.
- Establish and enforce best practices in coding, design, testing, and deployment of AI systems.
- Work closely with data scientists, software engineers, UI/UX designers, and product managers to translate business requirements into technical deliverables.
- Maintain high standards for code quality, system reliability, and solution scalability through rigorous code reviews and testing protocols.
- Oversee the end-to-end project lifecycle, ensuring timely delivery of milestones and alignment with client objectives.
- Serve as the technical point of contact for clients, providing regular updates, technical guidance, and aligning deliverables with business goals.
- Identify opportunities for process optimization and technological innovation within the AI chatbot domain.
Must-Have Skills
- Generative AI expertise, with a proven track record in designing and developing solutions using GenAI models and architectures.
- Hands-on experience with Agentic AI systems, including multi-agent orchestration and workflow automation.
- Extensive experience implementing conversational flows and logic with the LangGraph framework.
- Deep understanding and practical application of Model Context Protocol for managing context and state in large language model deployments.
- Advanced proficiency in Python, including experience with AI/ML libraries and frameworks.
- Demonstrated ability to lead, mentor, and inspire technical teams to achieve high performance and deliver quality outcomes.
- Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
Good-to-Have Skills
- Understanding of data modeling, data pipeline design, and scalable data architecture principles.
- Familiarity with user interface and user experience design as it relates to conversational AI applications.
- Experience deploying AI solutions on major cloud platforms such as Azure, AWS, or GCP.
- Knowledge of CI/CD pipelines, containerization, and infrastructure automation is a plus.
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