Artificial Intelligence Engineer

Skills:

• 7-9 years of software engineering experience with 5+ years in AI/ML development.
• Hands-on experience in Machine Learning, Deep Learning, and Generative AI (LLMs, RAG, AI agents) with enterprise use case delivery.
• Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch) with experience building production-grade AI applications and APIs.
• Ability to design and implement scalable, microservices-based AI solutions integrated with enterprise systems.
• Experience with Azure/AWS/GCP AI services, containerization (Docker), and cloud-native deployment models.
• Practical experience in model deployment, CI/CD pipelines, monitoring, and lifecycle management of AI solutions.
• Strong understanding of data pipelines, ETL, vector databases, and enterprise data integration for AI applications.
• Proven ability to lead small AI teams, manage Agile delivery, and ensure high-quality, timely execution of AI projects.

Responsibilities:

• Lead end-to-end AI solution delivery by defining architecture standards, driving innovation, and enabling reusable frameworks.
• Design and govern scalable, secure AI/GenAI architectures ensuring seamless integration and high performance.
• Lead and mentor AI teams while ensuring high-quality, timely, and standards-driven project delivery.
• Drive development and adoption of GenAI solutions including copilots, RAG systems, and AI agents with robust evaluation and guardrails.
• Establish and operationalize MLOps/LLMOps practices for reliable, automated, and scalable AI lifecycle management.
• Collaborate with stakeholders to translate business needs into AI solutions and effectively communicate technical decisions.
• Enforce responsible AI practices, governance frameworks, and compliance across AI solution delivery.