• Act as a trusted advisor by conducting workshops, gathering requirements, and presenting solutions to both technical and business audiences. • Design and implement Azure-based data solutions using Microsoft Fabric, Azure Synapse Analytics, Databricks, and Azure database systems (SQL, Cosmos DB, Postgres). • Build robust ETL/ELT pipelines to ingest, transform, and integrate large volumes of structured and unstructured data from diverse sources. • Leverage Azure AI Services, Azure OpenAI, Azure Machine Learning, and Cognitive Services to deliver intelligent business solutions. • Collaborate with architects to design scalable, secure, and high-performance Azure Data & AI architectures. • Implement version control, CI/CD pipelines, and automation using Azure DevOps, GitHub Actions, and Infrastructure as Code tools (Bicep, Terraform). • Ensure compliance with data governance, privacy, and security requirements including RBAC, encryption, and identity management. • Develop advanced reporting and interactive dashboards with Power BI to deliver actionable insights to stakeholders. • Mentor junior team members, contribute to internal best practices, and stay current with Azure Data & AI innovations.

• Lead the development of Data and AI strategies and roadmaps, aligning technology solutions with business goals and driving digital transformation initiatives. • Design and architect advanced Azure solutions integrating Microsoft Fabric, Azure Synapse Analytics, Databricks, Azure SQL/Cosmos DB/Postgres, and AI technologies to meet complex enterprise requirements. • Provide technical guidance and mentorship to engineering teams, ensuring best practices in solution development, deployment, and operational excellence. • Oversee the integration of Data and AI solutions with existing enterprise systems and processes, ensuring seamless interoperability, data flow, and security compliance. • Design and implement enterprise data architectures that support AI solutions, leveraging advanced database systems and ensuring data quality, governance, and security. • Architect solutions leveraging Azure AI Services, Azure OpenAI, Azure Machine Learning, and Cognitive Services to deliver intelligent business capabilities. • Partner with Project Managers and stakeholders to manage complex projects from inception to completion, ensuring timely delivery and alignment with business objectives. • Mentor and coach team members, fostering a culture of continuous learning, innovation, and technical excellence within the organization. • Develop and improve deployment architectures, solution standards, and technical frameworks that guide organizational excellence. • Act as a trusted technical advisor to clients, conducting executive workshops, presenting solutions, and driving consensus on technical approaches.

• Serve as Zencore’s senior-most technical authority on the practical application of advanced artificial intelligence and machine learning. • Partner with the sales and business development teams in a pre-sales capacity to scope opportunities, design solutions for proposals, and act as the senior technical voice in client pitches. • Lead the architecture and design of sophisticated, secure, and scalable AI solutions for our clients, moving beyond standard API integrations to create genuine competitive advantages. • Collaborate closely with Cloud & Data Architects to guarantee the design and deployment of comprehensive client solutions. • Address the growing European demand for private, data-sovereign AI by designing systems that meet strict GDPR and data privacy requirements. Strive for model explainability and bias mitigation, ensuring solutions adhere to ethical standards and European safety guardrails. • Architect solutions for hosting, fine-tuning, and optimizing both proprietary (e.g., Gemini, Claude) and open-source (e.g., Llama, Mistral) models on hyperscaler platforms. • Lead clients in selecting optimal cloud-native technologies, prioritizing Google Cloud solutions for deploying and scaling production-grade agentic systems. • Guide and mentor customers and Zencore's engineering teams on advanced topics, establishing best practices for high-performance training (PyTorch, JAX, TPUs), efficient model serving (vLLM), and complex agentic systems (LangGraph, Langchain, Google ADK). • Devise the financial architecture of AI solutions by performing ROI analysis and implementing cost-optimization strategies to ensure large-scale deployments remain economically sustainable for customers. • Act as an external thought leader, contributing to the Zencore brand through blog posts, conference presentations, and community engagement. • Act as a "player-coach," providing hands-on leadership and fostering a culture of deep technical excellence in AI/ML.

• Design, develop, and optimize machine learning and deep learning models for AI agent use cases. • Build intelligent systems capable of reasoning, prediction, automation, and decision support. • Apply NLP, data analysis, and agentic workflows to solve complex CX and operational challenges. • Manage, clean, and preprocess large datasets to extract meaningful features. • Train, evaluate, and fine-tune machine learning models to meet performance and reliability standards. • Continuously monitor and improve model accuracy, robustness, and efficiency. • Deploy AI models into production environments with a focus on scalability, performance, and reliability. • Collaborate on MLOps practices to support continuous integration, monitoring, and improvement. • Ensure AI systems integrate smoothly with existing platforms and workflows. • Work closely with data scientists, software engineers, product managers, and domain experts. • Translate business problems into effective AI solutions with measurable outcomes. • Contribute to solution design for enterprise pilots and long-term deployments. • Ensure AI solutions comply with ethical standards, data privacy requirements, and legal regulations. • Document models, algorithms, workflows, and decisions clearly for internal and external stakeholders. • Stay up to date with the latest AI research, tools, and best practices; and apply them where valuable.