About the Role
About the Role
We are looking for a Senior AI Engineer to help build next-generation intelligent data platforms that enable AI-driven analytics, automation, and business insights across enterprise systems. This role focuses on combining AI, data engineering, and modern metadata-driven architectures to create scalable and reusable data solutions.
You will work on designing intelligent pipelines, integrating Large Language Models (LLMs), building semantic and metadata frameworks, and developing AI-assisted data transformation capabilities that support analytics and decision-making across the organization.
This is a hands-on senior engineering role ideal for someone who enjoys solving complex platform challenges, building scalable systems, and driving innovation in AI-enabled data ecosystems.
Key Responsibilities
- Design, develop, and maintain AI-powered data pipelines and services for automation, metadata enrichment, schema understanding, and intelligent data transformation.
- Build and integrate LLM-based applications and AI services using modern orchestration and agent frameworks.
- Develop scalable Python-based microservices, APIs, and data-processing workflows.
- Create reusable data models, semantic frameworks, and metadata-driven architectures to support enterprise analytics and reporting.
- Design and optimize ETL/ELT pipelines, data integration workflows, and star-schema generation processes for structured and unstructured data sources.
- Implement intelligent data discovery, mapping, and transformation solutions across heterogeneous enterprise systems.
- Collaborate with data architects, analysts, governance teams, and business stakeholders to align technical solutions with business objectives.
- Establish engineering best practices for scalability, observability, performance, security, testing, and deployment.
- Support cloud-native and distributed data platforms using modern data engineering and AI technologies.
- Mentor engineers, participate in code reviews, and contribute to technical leadership and architectural decisions.
Required Qualifications
- 6+ years of experience in software engineering, AI engineering, or data engineering roles.
- Strong proficiency in Python and modern backend development practices.
- Hands-on experience building AI/LLM-powered applications or intelligent automation solutions.
- Experience with modern AI frameworks, orchestration tools, or agent-based architectures.
- Solid understanding of data engineering concepts including ETL/ELT pipelines, data modeling, metadata management, and analytics platforms.
- Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
- Familiarity with scalable data platforms, APIs, distributed systems, and microservices.
- Strong analytical, problem-solving, and communication skills.
