Sr. AI & Data Expert

Overview:

The Sr. AI & Data Expert is a highly skilled individual contributor responsible for designing and implementing advanced AI systems and scalable data platforms. This role focuses on building next generation AI solutions—including agentic AI systems, LLM-based applications, and industrial data pipelines—that transform data into actionable business outcomes. The position requires deep expertise across AI/ML, data engineering, and cloud platforms, along with the ability to translate business needs into technically robust and production-ready solutions.

Key Responsibilities:

• Design and implement agentic AI systems, including multi-agent frameworks and autonomous workflows
• Develop and optimize RAG pipelines, LLM integrations, and model fine-tuning for real-world applications
• Build production-grade AI services and APIs, ensuring scalability, performance, and reliability
• Design and implement scalable data architectures for structured and unstructured data
• Build and maintain data pipelines supporting ingestion, processing, and consumption layers
• Ensure data quality, consistency, and availability across AI and analytics workloads
• Troubleshoot and resolve complex technical challenges across AI, data, and platform layers
• Optimize systems for performance, latency, and cost efficiency, especially in high-scale environments
• Contribute to reusable components, frameworks, and engineering best practices
• Implement and maintain end-to-end ML/LLM lifecycle workflows, including training, deployment, and monitoring
• Integrate CI/CD pipelines for AI systems and automate model validation, testing, and releases
• Monitor model performance, drift, and system health in production
• Design and deploy AI/data solutions across multi-cloud or hybrid environments, including GPU-based workloads
• Work with modern infrastructure stacks to support scalable AI processing and storage
• Ensure efficient utilization of compute resources and cloud services
• Apply data governance, security, and compliance standards, including data sovereignty requirements
• Implement Responsible AI practices, ensuring transparency, fairness, and secure model usage
• Contribute to defining guardrails for safe and compliant AI deployment
• Translate business requirements into AI and data solutions aligned with KPIs and measurable outcomes
• Collaborate with product, engineering, and business teams to deliver end-to-end solutions
• Provide technical input to support decision-making and solution design
• Contribute to documentation, standards, and reusable assets.

Qualifications:

Education:

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Master’s degree is a plus.

Experience:

• 10–14 years of experience in AI/ML, data engineering, or related domains
• Strong hands-on experience building and deploying AI/ML systems in production
• Experience with LLMs, RAG pipelines, and modern AI frameworks
• Exposure to large-scale data platforms and distributed systems
• Experience working in cloud environments (multi-cloud preferred)

Skills & Competencies:

• AI/ML development (LLMs, RAG, model fine-tuning)
• Data engineering and pipeline development
• MLOps / LLMOps practices and tooling
• Backend development (Python and related frameworks)
• Distributed systems and scalable architectures
• AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain or similar)
• Data processing tools (e.g., Spark, Airflow, Prefect)
• Containerization and orchestration (Docker, Kubernetes)
• Cloud platforms (AWS, Azure, GCP)
• Observability and monitoring tools