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.

Preferred Qualifications

• Experience with knowledge graphs, semantic technologies, metadata platforms, or enterprise data modeling.
• Familiarity with MLOps, LLMOps, model evaluation, AI observability, or responsible AI practices.
• Experience with Spark, Lakehouse architectures, or modern analytics ecosystems.
• Exposure to containerization, CI/CD pipelines, and cloud-native deployment patterns.
• Experience building AI-enabled analytics, search, recommendation, or natural language query solutions.

Technologies & Skills

• Python
• Large Language Models (LLMs)
• AI/ML Frameworks
• Agentic AI / AI Orchestration
• Data Engineering
• ETL / ELT Pipelines
• Cloud Platforms (Azure, AWS, GCP)
• APIs & Microservices
• Distributed Systems
• Metadata & Data Modeling
• Spark / SQL / Analytics Platforms