Job Title

Title - AI Engineer Type - Contract Location - Remote Roles and Responsibilities: - Vision & Strategy: Develop and continuously refine the long-term vision for driving innovation, user-centricity, and strategic alignment with broader business goals. - AI & System Architecture: Lead the design and development of the AI-driven architecture, ensuring scalability, robustness, and cutting-edge technology integration across machine learning, NLP, data pipelines, and automation components. - Team Leadership & Mentorship: Guide and inspire a team of AI engineers, machine learning specialists, and product developers, fostering a collaborative, innovative environment that encourages continuous learning and growth. - Cross-Functional Collaboration: Partner closely with stakeholders from product, design, engineering, and business units to ensure the roadmap aligns with business needs and delivers tangible value. - Platform Innovation: Keep the platform at the forefront of technology by incorporating emerging trends in agentic AI, multi-modal interfaces, generative AI, and autonomous orchestration. - Quality & Performance Optimization: Establish benchmarks for platform performance, reliability, and security. Regularly review and refine core systems to ensure peak performance and user satisfaction. - User Experience Focus: Drive a user-first approach, ensuring that functionality and interface support intuitive and seamless interactions for employees, partners, and customers. - Vendor & Technology Management: Evaluate and manage strategic relationships with third-party vendors, especially in areas like NLP, Microsoft integrations (e.g., Copilot), and cloud infrastructure (Azure), to leverage the best available technology. Qualifications: - Education: Advanced degree (PhD preferred) in Computer Science, AI, Machine Learning, or a related field. - Experience: 3-5 years of experience in AI/ML - AI Expertise: Deep knowledge of machine learning techniques, NLP, LLMs, and data-driven AI architectures, with hands-on experience designing and deploying complex AI systems. - Communication: Excellent communication skills with the ability to translate complex AI concepts into strategic roadmaps and actionable plans, tailored to both technical and non-technical stakeholders. - Strategic Mindset: Strong analytical and strategic thinking skills, with the foresight to anticipate future AI trends and an understanding of how to apply them to a multi-functional platform. Tools and Technologies: - AI Development Tools: Proficiency with AI development tools and frameworks such as Azure ML, PyTorch, TensorFlow, LangChain, and transformer-based models. - Cloud Infrastructure: Experience in using cloud-based AI and data infrastructure, particularly with Azure and Kubernetes. - Model Optimization: Familiarity with tools for managing and optimizing AI models in production (e.g., Milvus for vector search, Graph API for MS integrations). - System Design: Expertise in designing scalable, secure, and fault-tolerant AI systems, including familiarity with microservices, API management, and real-time data processing. Preferred Skills: - Industry Knowledge: Experience within a large, matrixed organization, preferably in technology or a related industry. - Multi-Modal Systems: Knowledge of systems integrating chat, voice, visual data, and embedded dashboards is a plus. - Enterprise AI Deployment: Familiarity with compliance, governance, and scalability considerations in deploying AI in enterprise environments. - Project Management: Skilled in project planning, prioritization, and resource allocation within an agile development environment.