Senior Applied AI Engineer
Summary
Build production-ready AI apps for enterprises using LLMs, RAG, AI agents and workflow automation, integrating them into existing systems.
Role Overview
We are looking for a Senior Applied AI Engineer to design and develop practical AI solutions for enterprise clients.
The role focuses on building production-ready AI applications using large language models, RAG, AI agents and workflow automation, and integrating these capabilities into existing enterprise systems.
Key Responsibilities
Design and develop enterprise AI applications using large language models.
Build RAG systems, AI assistants, AI agents and workflow automation solutions.
Integrate AI models with enterprise applications, databases and third-party APIs.
Develop prompt workflows, structured outputs and tool-calling functions.
Design document processing, embeddings, vector search and retrieval pipelines.
Implement AI evaluation, testing and guardrails.
Optimise AI performance, reliability, latency and operating cost.
Develop backend APIs and supporting services for AI applications.
Work closely with solution architects, business analysts and developers on project delivery.
Support deployment, monitoring, troubleshooting and continuous improvement of AI systems.
Requirements
Bachelor’s degree in Computer Science, Artificial Intelligence, Information Technology or a related field.
At least 3 years of relevant professional experience in AI engineering, machine learning, data engineering or enterprise AI application development.
Strong programming skills in Python.
Hands-on experience with LLM-based application development.
Experience with OpenAI API, Anthropic API, Amazon Bedrock or similar AI platforms.
Practical experience with RAG, embeddings and vector databases.
Experience with structured outputs, function calling or tool calling.
Strong understanding of APIs, databases and backend application development.
Experience with AWS, Azure or Google Cloud.
Good problem-solving and communication skills.
Preferred Skills
Amazon Bedrock
LangGraph, LangChain or similar frameworks
PostgreSQL and pgvector
Amazon OpenSearch
Vector databases
FastAPI
Document parsing and data ingestion pipelines
AI evaluation and regression testing
Prompt injection protection and AI guardrails
AWS Lambda, S3, DynamoDB, SQS and Step Functions
Docker and CI/CD