What You'll Be Doing?

AI System Architecture & Leadership (50%) :

- Design large-scale AI architectures that support real-time, AI-driven decision-making.

- Lead the development of AI-powered agent systems, focusing on LLMs, RAG, and knowledge-based AI.

- Define and execute Hivels AI strategy, identifying opportunities for new AI-powered product lines.

- Hire, mentor, and grow an AI engineering team, setting best practices for AI development.

- Conduct technical reviews, strategic planning, and AI innovation roadmaps.

- Establish AI governance frameworks.

Hands-On AI Engineering (50%) :

- Architect, develop, and deploy AI-powered agent architectures using deep learning, transformers, and reinforcement learning.

- Implement real-time AI inference systems, focusing on vector search, knowledge graphs, and multi-agent AI frameworks.

- Optimise AI pipelines for scalability, cost-efficiency, and low-latency inference.

- Work with AWS, Azure, or GCP to build and deploy production-grade AI models.

- Experiment with AutoGPT, CrewAI, OpenAI Function Calling, and LangChain to explore novel AI use cases.

- Conduct rapid proof-of-concepts (PoCs), iterate based on performance, and deploy cutting-edge AI features.

Key Responsibilities :

AI Architecture & Development :

- Build scalable AI agent frameworks that enhance software automation.

- Integrate retrieval-augmented generation (RAG) to enhance AI-driven decision-making.

- Work with large-scale vector databases (FAISS, Pinecone, Weaviate) for efficient knowledge retrieval.

- Develop multi-agent AI systems, leveraging LLMs, reinforcement learning, and prompt orchestration.

Leadership & Strategy :

- Define technical roadmaps and architectural best practices for AI-driven products.

- Partner with cross-functional teams to align AI strategies with business goals.

- Lead AI-focused technical reviews, sprint planning, and innovation discussions.

- Drive team growth, hiring, and mentorship for AI engineers.

Qualifications :

Experience & Technical Expertise :

- Overall 7+ years of experience and 3+ years of AI/ML experience with a track record of designing AI-powered applications.

- Proven leadership experience, managing AI teams and mentoring engineers.

- Deep learning, NLP, and generative AI expertise, including LLMs, transformers, and reinforcement learning.

- Strong experience with Python, PyTorch, TensorFlow, and AI/ML libraries.

- Hands-on knowledge of real-time AI processing, cloud AI deployments, and knowledge retrieval systems.

- Proficiency in MLOps best practices, including model retraining, AI observability, and scalable AI architectures.

Nice-to-Have Skills :

- Experience with multi-agent AI architectures (AutoGPT, CrewAI, LangChain, OpenAI Function Calling).

- Experience launching AI-driven SaaS products or enterprise AI solutions.

- Familiarity with multi-modal AI, combining text, vision, and structured data.