Lead AI Engineer
- Lead the hands-on design, coding, and deployment of complex AI-based solutions, from proof-of-concept to production. Ensure solutions are scalable, maintainable, and deliver measurable business value.
- Architect and build reusable, shared components for our internal "Unified Agent Platform." Create documentation, examples, and starter kits to empower the broader product and engineering community to build their own AI-powered features.
- Act as a go-to expert for AI development. Mentor other engineers on the team and across the organization, providing guidance on best practices, new tools, and effective implementation of AI technologies.
- Proactively research, experiment with, and master emerging AI technologies and frameworks for the purposes of evaluating for future use and/or to build POCs. Maintain a deep understanding of the evolving landscape to ensure our solutions remain cutting-edge.
- Demonstrate a strong curiosity for leveraging AI to improve personal and team productivity. Actively find and implement AI-powered tools and workflows to make your own role and development processes more efficient.
- Diagnoses complex problems and lead/coordinate cross team collaboration to resolve.
- Act as subject matter expert in focus area(s) and acts as a lead role for both onshore and offshore vendor/supplier development teams
- Bachelor's or Master's degree in a relevant field of work or an equivalent combination of education and work-related experience.
- Typically, a minimum of 10+ years of progressive work-related experience with demonstrated proficiency in multiple disciplines, technologies, or processes related to the position.
- Experience working with a set of geographically dispersed team and bringing a holistic view of development projects.
- Proven experience in a senior or lead engineering role (e.g., Lead Developer, Principal Engineer, Senior Software Engineer) with a focus on building and shipping production-grade software.
- Demonstrated track record of designing and building architecturally sound solutions , with a strong grasp of system design, API development, and data modeling.
- Significant hands-on experience in developing and deploying AI/ML-powered applications.
- A history of mentorship and technical leadership, with a talent for explaining complex topics to diverse audiences.
- An innate curiosity and a portfolio or history that demonstrates a commitment to continually learning new technologies as they evolve.
- Deep understanding of modern AI concepts, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic workflows.
- Hands-on experience with major generative AI platforms and models. Direct experience building solutions with the Google Gemini family of models is preferred.
- Expert-level proficiency in Python and common AI/ML libraries (e.g., TensorFlow, PyTorch, LangChain, Hugging Face).
- Strong experience with a major cloud provider (GCP, AWS, Azure), including their AI/ML services. Familiarity with MLOps principles and tools for CI/CD, model deployment, and monitoring.
- Solid understanding of microservices architecture, API design (e.g., REST, gRPC), and containerization technologies (e.g., Docker, Kubernetes).
- Strong analytical and problem-solving skills
- Ability to display effective verbal and written communication skills when explaining complex technical issues to a variety of technical audiences, including clients, vendors, senior management and staff.
- Ability to establish and maintain a high level of customer trust and confidence in the software engineering team's knowledge of the customer's business needs. Understands and implements work effectively utilizing agile best practices.
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