Senior AI Engineer (WFH)

Job description:The Senior AI Engineer leads the design, development, and deployment of advanced AI solutions, leveraging cutting-edge machine learning and data analytics techniques to drive business impact. This role requires hands-on expertise in AI model development, cloud-based AI services, and the ability to translate complex technical concepts into actionable solutions.Key Competencies:Microsoft Certification in Data & AI.Advanced experience with Microsoft Azure, Azure AI Services, GitHub, and Power BI.Strong analytical, problem-solving, and critical-thinking skills.Proficiency in Python and experience building AI applications and production-ready machine learning models.Proven experience in deploying AI solutions in business-critical applications.Exceptional communication skills, with the ability to articulate complex AI concepts to technical and non-technical stakeholders.Roles and Responsibilities:1. Data Management & Analytics:Design, optimize, and oversee robust data pipelines and ETL processes.Analyze complex, large-scale datasets to extract actionable insights and visualize findings through Power BI dashboards and reports.Leverage Microsoft Azure for efficient data storage, processing, and advanced analytics.2. AI & Machine Learning Development:Lead the architecture, development, and deployment of machine learning and AI models using Azure AI services.Translate business requirements into AI-driven solutions, integrating capabilities such as vision, speech, language, search, and predictive analytics into enterprise applications.Ensure models are interpretable, scalable, and aligned with business objectives.3. Integration & Deployment:Embed AI capabilities seamlessly into existing software systems and enterprise workflows.Deploy high-performance, scalable models and monitor their effectiveness in production environments.4. Strategic Guidance & Continuous Learning:Keep abreast of emerging trends and best practices in AI, machine learning, and data science.Mentor team members, provide guidance on best practices, and promote knowledge sharing within the team.Maintain certifications and continuously enhance technical expertise to address evolving business challenges.5. Collaboration & Leadership:Work closely with data engineers, developers, and business stakeholders to drive project success.Lead initiatives, influence technical direction, and contribute to the overall AI strategy of the organization.