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.

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.

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.

Principal Artificial Intelligence Engineer - Python Programming

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