[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_76":77,"_78":79,"_80":81,"_82":83,"_84":-7,"_85":-5,"_86":-5},"routes/_public.jobs._index",{"_9":10,"_11":12,"_13":-5,"_14":15},"jobsData",{"_22":23,"_24":25,"_26":27},"featuredJobs",[],"featuredCompany","categories",[16,17,18,19,20,21],"Creative & Design","Marketing & Communications","Operations & Strategy","Production","Sales & Business Development","Writing & Editing","jobs",[28],"nextPageToken","","total",1,{"_29":30,"_31":32,"_33":34,"_35":36,"_37":38,"_39":40,"_41":30,"_42":43,"_44":25,"_45":25,"_46":34,"_47":25,"_48":49,"_50":51,"_52":53,"_54":20,"_55":56,"_57":58,"_59":43,"_60":61,"_62":63,"_64":65,"_66":67},"remoteAllowed",false,"publishedAt",["D",1776322800000],"displayLogo","https://www.mediabistro.com/public/images/desk-100x50.webp","companyName","Plentific","description","AI Applied Engineer\nAs an AI Applied Engineer, you will design, build, and deploy AI‑powered features and automation tools that transform how our users interact with our platform and improve internal operational efficiency. You’ll work across the stack to integrate AI capabilities—such as intelligent assistants, AI agents, and predictive systems—directly into our Python‑based applications, experimenting with new frameworks and deployment solutions along the way.

Your day‑to‑day will focus on building real, production‑grade AI systems that deliver measurable value—whether that’s automating property management workflows, creating decision‑support tools for our teams, or embedding natural language and vision capabilities into our products.

You’ll collaborate closely with product managers, data scientists, and other engineers, taking AI solutions from concept to scalable production deployment. You’ll have the freedom to explore cutting‑edge tools like

FastAPI ,

PydanticAI , LLM orchestration frameworks, while ensuring solutions are robust, maintainable, and secure.

Responsibilities

Develop and deploy AI‑powered features and services in our Python‑based stack (FastAPI and Django, DRF) and explore new frameworks (e.g. BentoML) for performance and scalability.

Build and integrate intelligent automation systems, AI agents, and decision‑support tools into core product workflows.

Implement and optimise LLM‑based systems, RAG pipelines, and AI agent architectures for complex property management workflows.

Work with cross‑functional teams to gather requirements, define AI use cases, and iterate quickly on prototypes.

Integrate complementary AI capabilities—such as voice processing, computer vision, and NLP—into customer‑facing and internal tools.

Ensure all AI applications and models adhere to security best practices, including input validation, secure handling of sensitive data (PII/confidential property information), and protection against prompt injection and other AI‑specific vulnerabilities.

Collaborate with MLOps and platform engineers to ensure models are deployed, monitored, and iterated in production environments.

Maintain clear documentation for AI systems, APIs, and workflows.

Stay on top of emerging AI frameworks and deployment tools, bringing forward innovative ideas for application.

Qualifications

Strong Python development background (5+ years preferred), with solid experience in FastAPI or Django and Django REST Framework.

Proven track record of building and deploying AI/ML‑powered applications in production environments.

Proficiency with async and streaming APIs, enabling efficient real‑time data processing and low‑latency AI service delivery in microservices (FastAPI, Django, Flask, or similar).

Strong understanding of context engineering practices, optimising prompts, memory, and retrieval strategies for LLM‑based systems.

Hands‑on experience with AI‑assisted development tools such as Cursor, Claude Code, Codex, and GitHub Copilot, focusing on AI specification‑driven approaches for technical analysis, code generation, and code review.

Hands‑on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace) and LLM orchestration tools (PydanticAI, LangChain, LangGraph, or similar).

Experience deploying ML models using containerised solutions (Docker, Kubernetes) and frameworks like BentoML or equivalent.

Familiarity with vector databases and retrieval pipelines for RAG architectures.

Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps tooling (MLflow, Kubeflow, or similar).

Familiarity with voice‑to‑text, IVR, and/or computer vision systems is a plus.

Strong understanding of software engineering best practices—testing, CI/CD, version control, code reviews.

Excellent problem‑solving skills and ability to collaborate in cross‑functional teams.

Benefits

A competitive compensation package

25 days annual holiday + 1 additional day for every year served up to 3 years.

Flexible working environment including the option to work abroad

Private health care for you and immediate family members with discounted gym membership, optical, dental and private GP

Enhanced parental leave

Life insurance (4x salary)

Employee assistance program

Company volunteering day and charity salary sacrifice scheme

Learning management system powered by Udemy

Referral bonus and charity donation if someone you introduce joins the company

Season ticket loan, Cycle to work, Electric vehicle and Techscheme programs

Pension scheme

Work abroad scheme

Company‑sponsored lunches, dinners and social gatherings

Fully stocked kitchen with drinks, snacks, fruit, breakfast cereal etc.

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