AI Engineer - Remote

You’ll design, build, and integrate advanced AI models into real software systems. This role sits at the intersection of software engineering, data science, and MLOps - turning research into robust, scalable, production-ready AI services. Core Responsibilities Model Engineering Build functional AI services from architectural designs

Orchestrate data ingestion, inference flows, and output pipelines

Optimise latency, memory, and throughput

Implement testing, validation, and error/bias analysis

Agentic Workflows Design multi-agent systems using LangChain, LangGraph, or Microsoft Agent Framework

Implement reasoning loops (e.g., ReAct)

Integrate tools, APIs, databases, and memory systems

Develop safety and reliability checks for agent behaviour

Data Engineering Build scalable ETL/ELT pipelines

Perform feature engineering and advanced data prep

Integrate SQL/NoSQL, data lakes, warehouses, and streaming APIs

Ensure compliance with GDPR/CCPA and internal governance

MLOps & Deployment Deploy AI services on Azure using REST APIs

Use Docker + Kubernetes for scalable production workloads

Build ML-focused CI/CD pipelines

Implement monitoring, drift detection, logging, alerting, and retraining

Manage infrastructure with Terraform

Experience 2+ years as an AI Engineer or Software Engineer with strong AI/ML exposure

Technical Skills Advanced Python (asyncio, type hinting, Pydantic)

Backend/API development with FastAPI/Flask/Django

Agentic frameworks (LangChain, LangGraph, Microsoft Agent Framework)

LLM orchestration, RAG, prompt engineering

Cloud (Azure preferred), Docker, Kubernetes

IaC (Terraform)

PostgreSQL, plus exposure to NoSQL and vector databases

CI/CD, monitoring, observability, ML-specific drift detection

Collaboration & Communication Work effectively with data scientists, PMs, and stakeholders

Communicate technical decisions clearly

Maintain strong documentation across pipelines and architectures