Applied AI Engineer - AI Labs

AI Labs is responsible for building and deploying next-generation AI-powered solutions across the organisation and for our clients. Our focus is on creating production-grade systems using Large Language Models (LLMs), intelligent agents, and retrieval-based architectures that automate workflows, enhance decision-making, and accelerate delivery across the enterprise. This role is hands-on and delivery-focused. The Applied AI Engineer will work on building, integrating, and scaling real-world AI systems rather than on model research or algorithm development.


Responsibilities:

  • Design, develop, and deploy AI-driven solutions using Large Language Models (LLMs) and related technologies.
  • Build and maintain Retrieval-Augmented Generation (RAG) pipelines, agent-based workflows, and AI orchestration layers.
  • Integrate LLM-powered capabilities into enterprise applications, internal tools, and client-facing platforms.
  • Develop prompt frameworks, tool-calling logic, and guardrails to ensure reliable, safe, and high-quality AI outputs.
  • Implement evaluation, monitoring, and feedback mechanisms to continuously improve accuracy, cost efficiency, and system performance.
  • Work closely with business stakeholders, product teams, and engineering teams to translate requirements into scalable AI solutions.
  • Document architectures, workflows, and implementation patterns to support maintainability and knowledge sharing.


Requirements:

  • Strong proficiency in Python and experience building API-driven applications.
  • Hands-on experience working with Large Language Model platforms (e. g., OpenAI, Anthropic, Groq, or similar).
  • Experience with prompt engineering, structured outputs (JSON, tool calling), and multi-step LLM workflows.
  • Experience with vector databases and embedding-based retrieval systems (e. g., FAISS, Pinecone, Weaviate, Chroma).
  • Familiarity with integrating AI systems with databases, APIs, and enterprise software.
  • Experience building or working with RAG pipelines, intelligent agents, or multi-model orchestration frameworks.
  • Understanding of performance, cost, and reliability trade-offs in production AI systems.
  • Familiarity with frameworks such as LangChain, LangGraph, CrewAI, or similar is a plus.
  • Experience deploying or operating AI-powered services on cloud platforms such as AWS, Azure, or GCP.
  • Familiarity with monitoring, logging, and maintaining production services is desirable.
  • Strong problem-solving and analytical skills with the ability to work on ambiguous, evolving AI use cases.
  • Ability to collaborate with cross-functional teams and communicate complex technical concepts clearly.
  • A proactive mindset with a strong interest in emerging AI technologies and applied innovation.
  • Comfortable working in a fast-paced, experimental environment where rapid iteration is expected.
  • 1-4 years of experience in software engineering, data engineering, or applied AI development.
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
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