Artificial Intelligence Engineer

About the Role

We're seeking an experienced AI Engineer with a strong software development background to design, develop, and deploy cutting-edge AI/ML solutions. You'll bridge the gap between research and production, building scalable AI systems that solve real-world problems, with a focus on modern agentic AI architectures and knowledge management systems.

Key Responsibilities

• Design and implement machine learning models and AI systems from concept to production

• Build and optimize ML pipelines, including data preprocessing, feature engineering, model training, and deployment

• Develop agentic AI systems with autonomous decision-making capabilities, tool use, and multi-step reasoning

• Design and implement RAG (Retrieval-Augmented Generation) systems using vector databases for efficient semantic search and knowledge retrieval

• Build Model Context Protocol (MCP) integrations to connect AI systems with external tools, data sources, and services

• Develop scalable AI applications using modern software engineering practices

• Collaborate with cross-functional teams to integrate AI capabilities into existing products and services

• Implement and optimize embedding pipelines for document processing and semantic search

• Monitor, maintain, and improve model performance in production environments

• Conduct experiments and research to evaluate new AI/ML techniques and frameworks

• Write clean, maintainable, and well-documented code following best practices

• Optimize model inference performance and resource utilization

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, or related field

• 3+ years of software development experience with proficiency in Python and at least one other language (Java, C++, Go)

• 2+ years of hands-on experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn)

• Strong understanding of ML fundamentals: supervised/unsupervised learning, deep learning, neural networks, NLP, computer vision

• Experience with vector databases (Pinecone, Weaviate, Chroma, Qdrant, or similar) and embedding models

• Understanding of agentic AI patterns including reasoning loops, tool use, planning, and self-correction

• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)

• Solid understanding of data structures, algorithms, and software design patterns

• Experience with version control (Git), CI/CD pipelines, and agile development methodologies

• Proven ability to take ML models from prototype to production

Preferred Qualifications

• Experience with LLMs and generative AI (GPT, Claude, Llama, etc.)

• Hands-on experience building agentic systems with frameworks like LangChain, LlamaIndex, AutoGPT, or CrewAI

• Experience implementing Model Context Protocol (MCP) servers and clients

• Knowledge of prompt engineering, few-shot learning, and chain-of-thought reasoning

• Experience with semantic search, chunking strategies, and hybrid retrieval systems

• Knowledge of MLOps tools and practices (MLflow, Kubeflow, Weights & Biases)

• Experience with distributed computing and big data technologies (Spark, Hadoop)

• Contributions to open-source ML projects or published research

• Experience with A/B testing and experimentation frameworks

• Background in building recommendation systems, search engines, or conversational AI

• Familiarity with multi-agent systems and agent orchestration patterns

Technical Skills

• Languages: Python, SQL, plus Java/C++/Go

• ML/AI: PyTorch, TensorFlow, Hugging Face, scikit-learn, OpenAI API, Anthropic API

• Agentic AI: LangChain, LlamaIndex, function calling, tool use, ReAct patterns

• Vector Databases: Pinecone, Weaviate, Chroma, Qdrant, Milvus, or pgvector

• MCP: Model Context Protocol implementation and integration

• Embeddings: OpenAI embeddings, Sentence Transformers, Cohere

• Data: Pandas, NumPy, data pipelines, feature stores

• Infrastructure: Docker, Kubernetes, AWS/GCP/Azure, REST APIs

• Tools: Git, Jupyter, Linux/Unix, monitoring and logging tools