Position Summary
We are seeking a highly experienced Senior AI Engineering Lead to drive the design, development, and deployment of advanced artificial intelligence solutions across the organization. This role will serve as both a senior technical leader and people manager, responsible for leading AI strategy execution, building production-ready AI systems, and guiding a team of AI and software developers.
The Senior AI Engineering Lead will be responsible for developing custom AI solutions that go beyond basic LLM API integration. This includes predictive modeling, Retrieval-Augmented Generation or RAG systems, agentic AI workflows, fine-tuned models, multimodal AI solutions, and scalable AI platforms that deliver measurable business impact.
This position requires strong hands-on technical expertise, leadership maturity, strategic thinking, and the ability to translate complex business needs into reliable, secure, and production-grade AI solutions.
Key Responsibilities
AI Strategy and Technical Leadership
- Lead the research, design, and implementation of AI and machine learning solutions aligned with business priorities.
- Provide technical direction for AI architecture, model selection, AI infrastructure, and production deployment.
- Evaluate emerging AI technologies, foundation models, agentic frameworks, and infrastructure tools to determine suitability for company use.
- Define technical standards, best practices, and governance for AI development, deployment, monitoring, and responsible use.
- Partner with product, engineering, data, and business leaders to identify high-value AI opportunities and translate them into executable roadmaps.
AI Development and Solutions Engineering
- Design and build custom AI products, including predictive models, RAG pipelines, agentic AI workflows, semantic search systems, and fine-tuned models.
- Develop AI-powered features and services that integrate with existing platforms, workflows, and business systems.
- Build and optimize LLM-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, OpenAI SDK, Anthropic SDK, and Model Context Protocol or MCP.
- Design embedding pipelines, vector database structures, hybrid search, re-ranking, and graph-augmented retrieval solutions.
- Lead development of multimodal AI solutions involving text, image, audio, structured data, and other domain-specific inputs.
Production AI and MLOps
- Lead deployment, monitoring, versioning, and continuous improvement of AI models in production environments.
- Build and maintain MLOps pipelines for model training, evaluation, deployment, retraining, and lifecycle management.
- Ensure AI systems are scalable, reliable, secure, explainable, and aligned with business and compliance requirements.