Job Overview:
We are seeking an experienced and visionary Fullstack Vertical AI Agent Solutions Lead to spearhead the design, development, and deployment of AI-driven solutions tailored to specific industry verticals. In this role, you will lead the end-to-end lifecycle of AI agent development — from data architecture to model deployment and user-facing applications — while working closely with product, engineering, and industry teams. The ideal candidate combines deep expertise in machine learning, fullstack software development, and product-oriented thinking to build intelligent, scalable, and domain-specific AI agent systems.
Key Reponsibilities:
- Lead the architecture and development of fullstack AI solutions (frontend, backend, and ML layers).
- Design and implement domain-specific (vertical) AI agents that solve real-world industry problems.
- Collaborate with product managers and industry experts to define solution requirements.
- Build robust data pipelines for training, fine-tuning, and updating AI models.
- Oversee deployment strategies, including APIs, cloud integration, and real-time serving.
- Ensure solutions are scalable, secure, and optimized for performance.
- Mentor and guide cross-functional teams of ML engineers, software developers, and data scientists.
- Stay ahead of AI research, emerging technologies, and vertical-specific trends.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or a related field.
- 5+ years of experience in machine learning, fullstack development, and solution architecture.
- Strong experience with ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
- Proficiency in backend (e.g., Python, Node.js) and frontend technologies (e.g., React, Next.js).
- Deep understanding of cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Proven experience building and shipping production-grade AI products.
- Excellent leadership, project management, and stakeholder communication skills.
Preferred Skills:
- Familiarity with Retrieval-Augmented Generation (RAG), LLM fine-tuning, or agent orchestration frameworks.
- Experience developing vertical-specific applications (e.g., healthcare, finance, logistics, education).
- Knowledge of Kubernetes, Docker, and serverless architecture.
- Strong product sense and a bias toward building user-centric AI solutions.