Senior AI Engineer

We are looking for an experienced Senior AI Engineer with strong expertise in Agentic AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Solution Architecture. This role requires someone who can design, architect, and build enterprise-scale AI applications while owning the end-to-end technical solution from ideation to production. The ideal candidate should have deep hands-on experience in building intelligent AI agents, designing scalable AI architectures, integrating enterprise systems, and delivering production-grade AI applications.

Responsibilities:

• Design and architect enterprise-grade AI applications using Agentic AI and Large Language Models (LLMs).
• Own the end-to-end technical design and architecture of AI-powered products.
• Build intelligent multi-agent systems using modern AI orchestration frameworks.
• Design and implement scalable RAG pipelines using vector databases and enterprise knowledge sources.
• Develop AI workflows integrating APIs, databases, enterprise applications, and cloud services.
• Collaborate with Product Managers, Engineering teams, and business stakeholders to translate business problems into AI solutions.
• Optimise AI applications for scalability, latency, accuracy, security, and cost efficiency.
• Define architecture standards, design patterns, and engineering best practices for AI platforms.
• Mentor engineers and provide technical leadership across AI initiatives.
• Stay updated with emerging AI technologies and evaluate their adoption within the organisation.

Requirements:

• 8+ years of overall software engineering experience.
• Strong hands-on experience in Agentic AI and enterprise AI application development.
• Proven experience designing and architecting production-grade AI solutions.
• Expertise with Large Language Models (OpenAI, Claude, Gemini, Llama, or similar).
• Strong experience building Retrieval-Augmented Generation (RAG) applications.
• Hands-on experience with AI orchestration frameworks such as LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, LlamaIndex, or similar.
• Strong proficiency in Python.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or similar.
• Experience deploying AI applications on AWS, Azure, or GCP.
• Strong understanding of REST APIs, Microservices, Docker, Kubernetes, and cloud-native architectures.
• Excellent problem-solving, communication, and stakeholder management skills.

Preferred Skills:

• AI Architecture and Solution Design.
• Prompt Engineering and AI Workflow Design.
• LLM Evaluation and Observability.
• AI Security and Governance.
• MLOps and CI/CD for AI applications.
• Knowledge Graphs and Semantic Search.
• Experience building enterprise-scale multi-agent AI systems.