AI Engineer
OpenMind
Published Date: • Remote
Description
OpenMind is seeking a skilled AI Engineer with at least four years of experience to join our innovative team. This role requires designing, developing, implementing, and maintaining advanced artificial intelligence solutions that automate processes, enhance business operations, and solve complex challenges. You will build AI-powered applications, integrate large language models, and develop intelligent automation systems while deploying AI solutions in dynamic production environments. This position also involves managing a small team of two, guiding collaborative efforts to drive the successful delivery of AI initiatives. As an AI Engineer at OpenMind, you will engage in end-to-end development of AI systems, combining deep expertise in Python programming, machine learning, and deep learning techniques. You will integrate cutting-edge technologies such as Retrieval-Augmented Generation, vector database management, and cloud AI platforms to build scalable and performant AI applications. Collaboration with cross-functional teams, including software engineers and product managers, is essential to align AI developments with business goals while ensuring responsible AI practices related to data privacy and security are strictly followed.
Responsibilities
- Design, develop, and deploy AI-powered applications and intelligent systems that meet business requirements and user needs.
- Integrate large language models such as GPT, Claude, and Gemini into various business applications to enhance functionality and intelligence.
- Develop AI agents, chatbots, virtual assistants, and automated workflows to improve customer engagement and operational efficiency.
- Utilize APIs, Python, and AI frameworks to build scalable, maintainable, and reliable AI solutions.
- Implement Retrieval-Augmented Generation techniques, embeddings, and manage vector databases to enhance data retrieval and AI model performance.
- Integrate AI models with existing software applications and business systems by collaborating with software engineering teams.
- Optimize AI models and applications for performance, accuracy, resource efficiency, and cost-effectiveness through iterative testing and evaluation.
- Lead a small team of AI specialists, coordinating tasks, mentoring, and fostering a collaborative working environment to ensure project success.
- Monitor, troubleshoot, and maintain deployed AI applications ensuring high availability and quick resolution of issues.
- Apply responsible AI practices including safeguarding data privacy, ensuring security compliance, and maintaining ethical standards in AI development.
- Develop and maintain machine learning operations (MLOps) pipelines for continuous integration and deployment of AI models.
- Design and manage data engineering workflows including ETL/ELT pipelines to prepare and process data for AI applications.
- Work with cloud AI platforms such as AWS, Azure, or Google Cloud to deploy and scale AI solutions.
- Utilize containerization tools like Docker and version control systems such as Git for efficient development and deployment workflows.
- Collaborate closely with data scientists, software engineers, and product teams to align AI development with strategic business objectives.
Experience
4 Years
Apply By
Required Skills
- Neural Network Development
- NoSQL Databases
- SQL Databases
- Google Cloud Platform
- Azure
- AWS
- Git
- Docker
- Google Gemini API
- Anthropic API
- OpenAI API
- Rest APIs
- FastAPI
- Python
- ETL/ELT Pipeline Development
- Tensorflow
- Machine Learning
- Deep Learning
- Generative AI and Large Language Models
- Retrieval-Augmented Generation
- Model Evaluation
- Data Engineering
- PyTorch
- Retrieval-Augmented Generation (RAG) Workflow Design
- Scikit-learn
- Vector Database Management
Nice to Have Skills
- PySpark
- MLOps pipeline orchestration
- Vector Database Integration (Pinecone, Weaviate, or FAISS)
- LangChain or LlamaIndex
- Cloud AI Platforms
- Deep Learning Model Training and Optimization
- LangGraph
- GPU-Accelerated Model Training
- MLOPS
- Prompt Engineering
- Langchain
- Azure Machine Learning
- Apache Spark