About the role
We are looking for a Senior Software Engineer (AI/ML) to design, develop, and scale intelligent applications powered by machine learning and generative AI. In this role, you will own end-to-end AI features from architecture and development to deployment, monitoring, and optimisation. You will collaborate closely with cross-functional engineering teams to integrate AI capabilities into production systems, build scalable backend services, and deliver high-quality solutions that create meaningful business impact.
Responsibilities:
- Design, develop, deploy, monitor, and maintain end-to-end AI/ML services and applications.
- Own complete modules and features throughout the software development lifecycle ("You build it, you own it").
- Integrate pre-trained machine learning and generative AI models into scalable backend services.
- Build and maintain production-ready APIs using Python frameworks such as FastAPI, Django, or Flask.
- Develop AI-powered applications leveraging LLMs, embeddings, vector databases, and prompt engineering techniques.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines and AI workflows.
- Collaborate with product managers, designers, and engineering teams to deliver scalable AI solutions.
- Develop and maintain CI/CD pipelines using GitHub Actions or similar tools.
- Build event-driven architectures using Kafka, RabbitMQ, or equivalent messaging platforms.
- Monitor production systems, troubleshoot issues, and continuously optimise performance and reliability.
- Stay updated with emerging trends and best practices in AI, machine learning, and generative AI technologies.
Requirements:
- 5+ years of software engineering experience.
- Minimum 2+ years of hands-on experience as an AI/ML/LLM engineer.
- Strong programming skills in Python.
- Solid understanding of AI/ML and generative AI concepts, including Large Language Models (LLMs), prompt engineering, context management, model inference, embeddings, vector databases, and KV caching.
- Hands-on experience with LangChain, LlamaIndex, or similar AI orchestration frameworks.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, or Keras.
- Experience developing backend services using FastAPI, Django, or Flask.
- Strong understanding of REST APIs and microservices architecture.
- Experience working with relational and NoSQL databases, including MySQL, MongoDB, Redis, and BigQuery (or equivalent).
- Experience integrating AI/ML/LLM capabilities into production applications.
- Hands-on experience with cloud platforms such as Google Cloud Platform (preferred) or AWS.
- Experience with CI/CD pipelines, preferably GitHub Actions.
- Experience working with event-driven systems using Kafka, RabbitMQ, or similar technologies.
- Strong debugging, problem-solving, and software design skills.
Preferred Qualifications:
- Experience building production-grade RAG applications.
- Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, Milvus, Weaviate, or Qdrant.
- Experience with Vertex AI, OpenAI, Gemini, Claude, Llama, or similar LLM platforms.
- Familiarity with Docker, Kubernetes, and containerised deployments.
- Experience implementing scalable AI systems with monitoring and observability.
- Understanding of MLOps best practices and model deployment pipelines.