We are looking for an experienced Principal Software Development Engineer AI (SDE IV) to lead the design, development, and delivery of enterprise-grade AI solutions.

The ideal candidate will have deep expertise in Agentic AI, Large Language Models (LLMs), and MLOps, along with a strong track record of leading technical teams and delivering AI-driven products from concept to production.

This role combines hands-on technical leadership with responsibility for driving the organization's AI Center of Excellence (CoE).

Key Responsibilities :

- Lead the design, development, and deployment of scalable AI/ML solutions and enterprise-grade Agentic AI applications.

- Define and execute the technical roadmap for the AI Center of Excellence, aligning AI initiatives with business objectives.

- Architect and implement LLM-powered applications, AI agents, RAG pipelines, and orchestration frameworks.

- Build and optimize ML/DL models, including training, fine-tuning, evaluation, and production deployment.

- Establish MLOps best practices for model versioning, deployment, monitoring, governance, and lifecycle management.

- Lead rapid prototyping, proof-of-concepts (PoCs), and pilot implementations for emerging AI use cases.

- Provide technical leadership, mentor AI engineers, and conduct architecture and code reviews.

- Collaborate with product, engineering, and business stakeholders to translate requirements into scalable AI solutions.

- Ensure AI solutions meet performance, reliability, security, and scalability standards.

- Evaluate emerging AI technologies and recommend innovative approaches to enhance enterprise AI capabilities.

Required Skills & Qualifications :

- Bachelor's degree in Computer Science, Engineering, or a related field.

- 6+ years of overall software development experience, including 5+ years of hands-on experience in AI/ML solution design and development.

- Proven experience leading AI engineering teams and managing multiple technical projects.

- Strong expertise in Agentic AI architectures, LLMs, RAG, prompt engineering, and AI orchestration frameworks such as LangGraph, LangChain, or similar.

- Hands-on experience with Python and AI/ML frameworks including PyTorch, TensorFlow, and Hugging Face.

- Strong understanding of MLOps, model deployment, monitoring, experiment tracking, and AI lifecycle management.

- Experience developing and deploying AI solutions on AWS, Azure, or GCP.

- Knowledge of vector databases, embeddings, and enterprise AI integration patterns is preferred.

- Excellent problem-solving, communication, stakeholder management, and technical leadership skills.