AI Engineer

Role Overview :

We are looking for an experienced AI Engineer with strong hands-on expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud platforms such as AWS, Azure or GCP.

The ideal candidate will be responsible for designing, developing and deploying AI-powered solutions, with a strong focus on Generative AI, LLM applications and scalable cloud-based AI systems.

Key Responsibilities :

- Design, develop and deploy AI/ML and Generative AI solutions for enterprise use cases.

- Build and implement LLM-powered applications using modern Generative AI frameworks and techniques.

- Develop RAG pipelines for enterprise knowledge retrieval and question-answering applications.

- Work with embeddings, vector databases, semantic search and document retrieval systems.

- Develop scalable AI applications and services using Python.

- Integrate LLMs with existing applications, APIs, data platforms and enterprise systems.

- Design and implement prompt engineering, context management and evaluation strategies.

- Deploy AI/ML solutions on AWS, Azure or GCP.

- Build production-ready AI services with appropriate monitoring, logging and performance optimisation.

- Collaborate with Data Scientists, ML Engineers, Data Engineers and product teams to translate business requirements into AI solutions.

- Evaluate LLM performance, response quality, latency and cost, and continuously optimise AI solutions.

- Stay updated with emerging developments in Generative AI, LLMs, RAG and AI engineering.

Required Skills :

- Strong hands-on experience with Python.

- Experience building Generative AI / AI applications.

- Strong understanding of LLMs and their practical implementation.

- Hands-on experience developing RAG-based applications.

- Knowledge of embeddings, vector databases and semantic search.

- Experience with at least one major cloud platform : AWS, Microsoft Azure, or Google Cloud Platform (GCP).

- Strong understanding of APIs, microservices and cloud-based application development.

- Experience with AI/ML model integration and deployment.

- Good understanding of software engineering principles, version control and development best practices.

Good to Have :

- Experience with frameworks such as LangChain, LlamaIndex or similar.

- Exposure to OpenAI, Azure OpenAI, Anthropic, Gemini or other LLM platforms.

- Experience with vector databases such as Pinecone, FAISS, Weaviate, Milvus or similar.

- Knowledge of Docker and Kubernetes.

- Experience with CI/CD and cloud-native deployments.

- Exposure to Agentic AI and AI agents.

- Experience with LLM evaluation, observability and responsible AI practices.

Key Competencies :

- Strong analytical and problem-solving skills.

- Ability to design scalable and production-ready AI solutions.

- Strong understanding of emerging Generative AI technologies.

- Ability to work collaboratively with cross-functional teams.

- Strong communication and technical documentation skills