We are partnering with a leading enterprise organization undergoing significant investment in Artificial Intelligence, Data, and Digital Innovation. They are looking for an experienced AI Engineer to design, build, and scale enterprise-grade Generative AI solutions that deliver measurable business impact.

This position will focus on developing production-ready LLM applications, Retrieval-Augmented Generation (RAG) platforms, AI agents, and intelligent automation services that enhance decision-making, operational efficiency, and customer engagement.

You will work at the intersection of AI, software engineering, cloud technologies, and data platforms, collaborating with multidisciplinary teams to take AI products from proof-of-concept through to enterprise-scale deployment.

Responsibilities of the Role:

• Design, develop, and deploy end-to-end Generative AI applications leveraging Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures.
• Build scalable AI platforms, APIs, and microservices that integrate AI capabilities into enterprise systems and business workflows.
• Develop and optimize document ingestion, processing, embedding generation, vector indexing, semantic search, and retrieval pipelines.
• Implement prompt engineering strategies, evaluation frameworks, AI guardrails, and monitoring tools to ensure reliability, accuracy, and responsible AI adoption.
• Design and maintain AI infrastructure, including vector databases, knowledge repositories, model serving environments, and deployment pipelines.
• Collaborate with software engineers, data scientists, product teams, and business stakeholders to deliver AI-driven solutions aligned with business objectives.
• Research and evaluate emerging AI technologies, open-source models, agentic frameworks, and best practices across the GenAI ecosystem.
• Optimize system performance across retrieval quality, latency, scalability, cost efficiency, and user experience through benchmarking and experimentation.
• Contribute to AI platform governance, security standards, compliance requirements, and responsible AI initiatives.
• Promote engineering excellence through CI/CD practices, MLOps frameworks, and cloud-native deployment methodologies.

Required Skills for the Role:

• Degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, or related discipline. Advanced qualifications are advantageous.
• Minimum 3 years of experience in AI Engineering, Machine Learning Engineering, Software Engineering, Data Science, or related technical domains.
• Proven experience designing and implementing production-scale Generative AI, LLM, RAG, or AI Agent solutions.
• Strong programming skills in Python with solid understanding of software engineering principles, system design, testing, and API development.
• Hands-on experience with modern AI frameworks and orchestration tools such as:
• LangChain
• LangGraph
• LlamaIndex
• Haystack
• Semantic Kernel
• Experience working with vector databases and semantic search technologies, including:
• Pinecone
• Weaviate
• FAISS
• Milvus
• Chroma
• Familiarity with leading AI ecosystems and foundation models, including OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Hugging Face, and open-source LLMs.
• Experience designing and deploying cloud-native applications on AWS, Azure, or Google Cloud Platform (GCP).
• Knowledge of MLOps, CI/CD pipelines, Kubernetes, Docker, and scalable model deployment architectures.
• Exposure to AI Agents, tool orchestration, function calling, Model Context Protocol (MCP), and multi-agent systems is highly advantageous.
• Strong SQL skills and foundational knowledge of data engineering concepts.
• Excellent communication skills.