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.
(ref:hirist.tech)
