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AI Engineer
Remote
US Time Zones (EST–PST)
Role Overview
We are looking for a hands-on AI Engineer to design, build, and deploy intelligent systems across a range of client environments. This is a technically deep role suited to someone who thrives at the intersection of machine learning, software engineering, and product thinking. You will work across the full AI development lifecycle — from prototyping and model integration to production deployment and ongoing optimisation. The ideal candidate is fluent in modern AI tooling, thinks in systems, and can translate complex technical concepts into scalable, working solutions.
Key Responsibilities
Design and build AI-powered features, pipelines, and automation workflows from scratch
Integrate and fine-tune LLMs, embedding models, and other ML systems into production applications
Develop and maintain RAG pipelines, vector search systems, and agent-based architectures
Write clean, well-structured code across backend and API layers to support AI feature delivery
Evaluate, benchmark, and iterate on model outputs to ensure quality and reliability
Collaborate with cross-functional teams to scope requirements and architect AI solutions
Stay current with the rapidly evolving AI landscape and proactively introduce relevant tooling and approaches
Document technical designs, system behaviour, and deployment processes clearly and thoroughly
Required Qualifications
Strong programming skills in Python; solid understanding of software engineering fundamentals
Hands-on experience building with LLMs (OpenAI, Anthropic, Mistral, or similar) via API and SDK
Practical experience with RAG architectures, vector databases (Pinecone, Weaviate, Chroma, etc.), and prompt engineering
Familiarity with AI agent frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI
Solid understanding of REST APIs and experience integrating third-party services and data sources
Ability to work autonomously in a fast-paced remote environment with minimal hand-holding
Must have prior remote work experience, be fluent with remote collaboration tools and platforms (such as Slack, Zoom, Google Workspace, Asana, or similar), and have ideally worked with US or UK-based companies. Applications without this experience will not be considered.
Preferred Qualifications
Experience with model fine-tuning, RLHF, or custom training workflows
Familiarity with MLOps tooling and model deployment pipelines (Docker, cloud functions, etc.)
Exposure to multimodal systems (vision, audio, or document understanding)
Background in data engineering or working with structured/unstructured data at scale
Contributions to open-source AI projects or a strong public portfolio of AI work
Tools & Technology
Python, REST APIs, and relevant AI/ML libraries
LLM platforms: OpenAI, Anthropic, Mistral, Hugging Face
Vector databases and embedding infrastructure
Agent frameworks: LangChain, LlamaIndex, CrewAI, or similar
Cloud infrastructure (AWS, GCP, or Azure)
Google Workspace, Slack, Zoom, and remote collaboration tools
Please note: It is crucial that you complete the application form in full. As part of the application process, you will be required to record a video. If your application is successful, you will receive an email confirming next steps — the video is the first step of the interview process. If you do not record a video, we will not be able to consider you for ANY open roles.
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