Company Profile - Celebal Technologies a Premier Microsoft Azure partner and have been recently funded by Norwest Venture Capital.

Celebal Technologies is a premier software services company in the field of Data Science, Big Data, Enterprise Cloud & Automation. Established in 2016, in this short span of time we grew to headcount of 2200+ We help in achieving a competitive advantage with intelligent data solutions, built using cutting-edge technology.

Job Summary: A highly skilled AI Engineer who leads the design, development, and governance of enterprise-grade AI solutions across multi-cloud environments, including Microsoft Azure and AWS. This role demands deep expertise in Microsoft technologies, strong proficiency in AI/ML frameworks, and hands-on experience in data engineering, MLOps, and scalable architecture design. This role is ideal for someone who thrives at the intersection of AI innovation, cloud engineering, and enterprise strategy.

Roles & Responsibilities:

• Design and deliver enterprise-grade AI/ML solutions across multi-cloud environments (Azure, AWS), ensuring scalability, security, performance, and seamless integration with existing technology ecosystems

• Define and enforce comprehensive AI governance frameworks addressing compliance (e.g., GDPR, EU AI Act), model risk, ethics, transparency, and explainability.

• Serve as a trusted advisor to business and technology leaders on AI strategy, emerging trends, and the long-term impact of AI on enterprise processes, platforms, and decision-making. • Lead end-to-end development and operationalization of AI solutions, including data exploration, model development, training, validation, deployment, and lifecycle management.

• Own and manage production operations of AI systems—covering monitoring, incident management, CI/CD pipelines, and release/change controls.

• Assess and evaluate change requests, effort, and impact across business functions, technology platforms, and governance controls to ensure strategic alignment and risk mitigation.

• Drive continuous improvement in model performance, system reliability, and AI delivery processes through rigorous testing, automation, and adherence to engineering best practices. • Partner with cross-functional teams (data engineering, application development, infrastructure, business units) to translate complex business challenges into actionable AI-driven solutions.

• Champion a culture of technical excellence and knowledge sharing by mentoring peers, reviewing code and architecture, and contributing to internal AI communities of practice.

• Other duties as required.

Required Skills & Experience:

• Bachelor's or master's degree in computer science, data science, information technology, or a related field, with 5+ years of experience in both AI/ML architecture and hands-on machine learning development.

• Strong foundation in machine learning and familiarity with deep learning techniques and frameworks.

• Demonstrated experience with MLOps and model lifecycle practices (training pipelines, monitoring, retraining, and CI/CD for ML).

• In-depth understanding of AI governance and responsible AI practices, including bias detection, model explainability, and alignment with global regulatory standards.

• Proven ability to design and scale AI solutions using cloud-native services across Azure (Azure Machine Learning, Azure OpenAI, Cognitive Services) and AWS.

• Proficient in Python and its ML ecosystem; experience integrating models into enterprise environments using APIs, containers, or microservices architectures.

• Proficient in Microsoft Power Platform components (e.g., Copilot Studio, Power Apps, Power Automate, Power BI, Dataverse) for embedding AI into low-code/no-code environments.

• Experience working with Microsoft development tools and stacks: Visual Studio, C#/.NET, JavaScript/TypeScript, SQL Server.

• Relevant certifications in Azure or AWS AI/ML tracks are strongly preferred.

• Strong communication and stakeholder management skills, with the ability to translate complex AI concepts into clear business insights and actionable roadmaps.

• Highly self-driven and accountable, with a demonstrated ability to lead in fast-paced, matrixed enterprise environments.