AI Engineer
The Bridge Ltd
Malvern, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Malvern, United States of America
Tech stack
Java
API
Artificial Intelligence
Amazon Web Services (AWS)
Software Applications
Azure
Cloud Computing
Computer Programming
Databases
Data Cleansing
DevOps
Github
Python
PostgreSQL
Machine Learning
MongoDB
MySQL
Natural Language Processing
Performance Tuning
Redis
TensorFlow
Software Engineering
SQL Databases
Google Cloud Platform
Enterprise Software Applications
Feature Engineering
PyTorch
Flask
Large Language Models
Prompt Engineering
Deep Learning
Model Validation
Generative AI
Backend
Gitlab
GIT
FastAPI
Containerization
Scikit Learn
Kubernetes
Information Technology
HuggingFace
GraphQL
Machine Learning Operations
Api Design
REST
Docker
Jenkins
Microservices
Job description
We are seeking a highly skilled AI Engineer to design, develop, and deploy AI-powered applications and machine learning solutions. The ideal candidate will have experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), cloud platforms, and modern AI frameworks. You will work closely with cross-functional teams to build scalable AI solutions that solve real-world business problems., * Design, develop, and deploy AI/ML and Generative AI applications.
- Build and optimize LLM-powered solutions using OpenAI, Claude, Gemini, or similar models.
- Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases.
- Create AI agents and workflow automation solutions.
- Fine-tune, evaluate, and optimize AI models for performance and accuracy.
- Build RESTful APIs and microservices to integrate AI capabilities into enterprise applications.
- Develop data preprocessing and feature engineering pipelines.
- Collaborate with data scientists, software engineers, and product teams.
- Deploy AI solutions on AWS, Azure, or Google Cloud Platform.
- Monitor, troubleshoot, and optimize AI applications in production.
- Follow MLOps best practices for model deployment, monitoring, and lifecycle management.
Requirements
- Python (Required)
- Java (Preferred)
- SQL
AI & Machine Learning
- Machine Learning
- Deep Learning
- Natural Language Processing (NLP)
- Generative AI
- Large Language Models (LLMs)
- Prompt Engineering
- AI Agents
- Fine-Tuning
- Model Evaluation
AI Frameworks & Libraries
- LangChain
- LangGraph
- LlamaIndex
- Hugging Face Transformers
- TensorFlow
- PyTorch
- Scikit-learn
- OpenAI API
- Anthropic Claude API
- Google Gemini API
RAG & Vector Databases
- Retrieval-Augmented Generation (RAG)
- Pinecone
- Weaviate
- ChromaDB
- FAISS
- Milvus
Cloud Platforms
- AWS
- Microsoft Azure
- Google Cloud Platform (Google Cloud Platform)
Databases
- PostgreSQL
- MongoDB
- MySQL
- Redis
DevOps & MLOps
- Docker
- Kubernetes
- Git
- GitHub/GitLab
- Jenkins
- MLflow
- Kubeflow
- CI/CD Pipelines
API & Backend
- FastAPI
- Flask
- REST APIs
- GraphQL
- Microservices, * Bachelor''''''''s or Master''''''''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
- 6+ years of software engineering experience with at least 2+ years in AI/ML or Generative AI.
- Strong proficiency in Python programming.
- Experience building and deploying production-grade AI applications.
- Hands-on experience with LLMs, RAG, and prompt engineering.
- Experience with cloud platforms and containerization technologies.
- Excellent analytical, problem-solving, and communication skills.