Full-Stack AI Engineer
🔒 Confidential Employer
Posted 8 May 2026
LOCATION
Remote
TYPE
Full-time
LEVEL
Mid-Senior level
CATEGORY
Software Engineering
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion
SKILLS
Python
PyTorch
TensorFlow
React
Node.js
Docker
Kubernetes
SQL
FULL DESCRIPTION
Full-Stack AI Engineer at [Employer hidden — sign up to reveal] (Remote, Full-time)
We are hiring a highly technical and execution-focused Full-Stack AI Engineer to build and deploy production-ready AI-powered applications. This role bridges full-stack software engineering, AI/ML integration, scalable infrastructure, and user-facing product development.
Responsibilities
- Deploy and integrate OpenAI models, Hugging Face models, fine-tuned LLMs, PyTorch/TensorFlow models
- Build scalable inference APIs using FastAPI, Flask, Node.js
- Develop AI copilots, chatbots, AI assistants, intelligent workflows
- Implement embeddings, vector search, RAG pipelines, semantic retrieval systems
- Work with Pinecone, Weaviate, FAISS, vector databases
- Build ETL/ELT pipelines for text, image, and structured data
- Automate preprocessing, labeling, transformations, versioning
- Orchestrate workflows using Airflow, Prefect, Dagster
- Manage datasets in Snowflake, BigQuery, Redshift
- Build modern front-end interfaces using React, Next.js, Vue
- Develop AI-powered user experiences: dashboards, assistants, analytics tools, AI workflows
- Design backend services and microservices
- Containerize applications with Docker, deploy into Kubernetes environments
- Build CI/CD pipelines for application releases, model deployments, infrastructure updates
- Monitor latency, cost, uptime, model drift using MLflow, Weights & Biases, Vertex AI, SageMaker, Kubeflow
- Implement secure APIs, authentication, permissions, access controls, rate limiting
- Ensure compliance with GDPR, HIPAA, SOC 2
- Work closely with product teams, data scientists, engineering teams
Required Experience & Skills
- 3+ years experience in software engineering, AI engineering, or ML-integrated systems
- Strong Python skills: PyTorch, TensorFlow, AI tooling
- Strong JavaScript/TypeScript skills: React, Node.js, frontend frameworks
- Experience deploying AI/ML models into production
- Experience with APIs, vector databases, RAG pipelines, embeddings
- Strong SQL and cloud data warehouse experience
- Experience with Docker and cloud infrastructure
Nice-to-Have
- AI-powered SaaS product development
- LLM fine-tuning and custom model workflows
- MLOps and model lifecycle management
- Microservices and serverless architectures
- Cost optimization for AI inference workloads
- Experience with Vertex AI, SageMaker, Kubeflow, LangChain, AI agents
- Startup or high-growth product experience
Interview Process
- Initial Phone Screen
- Video Interview with [Employer hidden — sign up to reveal] Recruiter
- Technical Assessment
- Client Interview(s) with Engineering Team
- Offer & Background Verification
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