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.
Key Responsibilities
- 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.
Required SkillsProgramming Languages
- 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
Qualifications
- 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.