Principal DATA & AI Solution Architecture

Job Summary

We are seeking a highly skilled and hands-on Principal AI Solutions Architect to design, build, and deploy end-to-end AI systems across the organization’s integrated value chain. This role is responsible for developing production-grade AI solutions, leveraging cloud-based platforms, and driving innovation across operations, supply chain, and enterprise systems.

The position requires strong expertise in machine learning, computer vision, optimization, and large-scale system design. The candidate will work closely with cross-functional stakeholders to translate business challenges into scalable AI solutions, ensuring measurable impact on performance and efficiency.

This is a hands-on role. The candidate is expected to write production-quality code, actively contribute to system implementation, and take ownership of delivering end-to-end solutions — not just design or propose architectures.

Key Responsibilities

1. Design and develop AI systems

• Design and build AI/ML solutions for large-scale operational environments
• Develop systems for time-series analysis, anomaly detection, and predictive modeling
• Implement computer vision solutions for inspection, monitoring, and quality control
• Optimize processes using data-driven and algorithmic approaches

2. Develop data-driven models and applications

• Build models using structured and unstructured data sources
• Apply predictive analytics and pattern recognition techniques
• Integrate domain-specific data into scalable machine learning pipelines

3. Build forecasting and optimization solutions

• Develop forecasting models using statistical, ML, or deep learning approaches
• Apply optimization techniques such as mathematical programming and heuristics
• Implement simulation and scenario-based decision systems

4. Develop enterprise AI and automation systems

• Build AI-powered applications for enterprise use cases
• Implement document understanding and information extraction solutions
• Develop GenAI/LLM-based systems such as RAG and intelligent assistants
• Automate workflows and integrate AI into enterprise platforms

5. Computer vision and advanced AI systems

• Develop detection, segmentation, and tracking models for industrial and operational use cases
• Build vision-language models for analytics, reporting, and knowledge extraction
• Deploy edge AI solutions for low-latency environments

6. Build and manage AI/ML platforms

• Develop and manage ML platforms for training, deployment, and monitoring
• Implement MLOps practices including experiment tracking and model registry
• Optimize model serving using modern inference frameworks
• Build scalable infrastructure using cloud and containerized environments
• Manage data pipelines and integration with enterprise systems

7. Collaborate and deliver production systems

• Write and maintain production-level code
• Own AI services end-to-end, including deployment and monitoring
• Collaborate with engineers and domain experts to deliver solutions
• Translate business requirements into deployable AI systems

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field
• 10+ years of experience in software engineering, AI, or machine learning
• Proven experience delivering production AI systems at scale
• Strong foundation in machine learning, optimization, and system design
• Experience with cloud platforms and distributed systems
• Proficiency in Python and at least one systems programming language (C++, Go, or Rust)
• Experience with MLOps, model deployment, and large-scale inference systems
• Strong problem-solving, analytical, and communication skills
• Ability to work across cross-functional teams and complex environments