Description

• Design, build, and maintain Model Context Protocol (MCP) servers and integrations that connect corporate data sources and internal systems to AI models and agent frameworks.
• 2. Develop and integrate Large Language Model (LLM) based solutions, including retrieval-augmented generation (RAG) pipelines, AI agents, and prompt orchestration layers, into corporate applications and workflows.
• 3. Build and maintain APIs (REST and/or GraphQL) that expose corporate data and AI capabilities as reusable Data Products and services for consumption by other teams and systems.
• 4. Design and implement AI-ready data pipelines, including data cleaning, transformation, and preparation processes, to make corporate data suitable for AI model consumption.
• 5. Support the development and operation of Data-as-a-Service (DaaS) offerings, ensuring reliable, secure, and scalable access to corporate data for downstream AI and business applications.
• 6. Collaborate with cross-functional teams (data architects, solutions architects, product owners, and business stakeholders) to translate business requirements into technical AI solutions.
• 7. Ensure that all AI solutions comply with Client data governance, security, and responsible AI standards.
• 8. Monitor, troubleshoot, and continuously improve the performance, reliability, and scalability of deployed AI solutions and integrations.
• 9. Stay current with emerging AI engineering practices, tools, and frameworks, and recommend improvements to the AI for Corporate technical roadmap

Key Skills

Education

Bachelor's degree