About the Role :

We are looking for an AI Engineer with hands-on experience in building and deploying AI-powered applications using Large Language Models (LLMs), Generative AI and modern AI frameworks. You will be responsible for designing, developing and integrating intelligent systems that solve real-world business problems through automation, conversational interfaces and AI-driven workflows. You will work closely with backend engineers, frontend engineers, product stakeholders and engineering leadership to take AI solutions from experimentation to production.

Key Responsibilities :

- Design, develop and deploy AI-powered applications using LLMs and Generative AI technologies.

- Build intelligent AI agents capable of executing multi-step tasks and interacting with external systems.

- Develop conversational AI solutions with context awareness, memory and natural language understanding.

- Design and implement Retrieval-Augmented Generation (RAG) pipelines.

- Integrate LLMs with external APIs, databases and third-party services.

- Build agentic workflows using tool calling, function calling and orchestration frameworks.

- Develop systems for processing, analysing and extracting insights from unstructured data.

- Implement prompt engineering techniques and optimise model performance.

- Evaluate AI outputs for accuracy, reliability, latency and cost.

- Implement appropriate guardrails, error handling and fallback mechanisms.

- Develop scalable APIs and services to integrate AI capabilities with existing applications.

- Monitor, troubleshoot and continuously improve AI applications in production.

- Stay up to date with emerging developments in LLMs, AI frameworks and agentic architectures.

Required Skills :

- 5 - 8 years of software engineering experience, with meaningful hands-on experience in AI/ML or Generative AI.

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

- Experience implementing MCP (Model Context Protocol) servers and clients.

- Familiarity with multi-agent architectures and agent orchestration.

- Strong programming experience in Python.

- Practical experience working with LLM APIs such as OpenAI, Anthropic or Google Gemini.

- Experience building applications using LLMs and Generative AI.

- Understanding of prompt engineering, context management and token optimisation.

- Hands-on experience with RAG architectures and vector databases.

- Understanding of embeddings, semantic search and information retrieval.

- Experience building REST APIs and integrating external services.

- Familiarity with asynchronous programming and event-driven architectures.

- Good understanding of software engineering principles, debugging and testing.

Good to Have :

- Experience taking applications from development to production.

- Experience with vector databases such as Pinecone, Qdrant, Weaviate or pgvector.

- Working knowledge of Node.js and TypeScript.

- Familiarity with PostgreSQL and relational database concepts.

- Experience with speech-to-text, text-to-speech and audio processing technologies.

- Experience with conversational AI platforms and chatbot development.

- Familiarity with Docker, AWS and cloud-based deployments.

- Experience with LLM evaluation frameworks, observability and monitoring.

- Exposure to open-source models and frameworks such as Hugging Face.

What We're Looking For :

- Strong problem-solving and analytical abilities.

- A practical engineering mindset with a focus on building working solutions.

- Ability to distinguish between problems that require AI and those better solved using conventional software engineering.

- Comfortable experimenting with new technologies and translating prototypes into production-ready systems.

- Ability to work independently and take end-to-end ownership.

- Strong understanding of system design, scalability and reliability.

- Ability to balance AI model quality, application performance and infrastructure costs.

- Good communication and collaboration skills.

- Comfortable working in a fast-moving product engineering environment.

What We Offer :

- Opportunity to build and deploy real-world AI-powered products.

- Hands-on exposure to LLMs, Generative AI and agentic architectures.

- Opportunity to experiment with emerging AI technologies and frameworks.

- A small, collaborative engineering team with significant ownership.

- Direct collaboration with engineering leadership and product stakeholders.

- Opportunity to influence technical architecture and engineering decisions.