Intermediate AI Engineer
Position Summary
Join our AI team as an Intermediate AI Engineer, where you'll build and deploy AI applications, agents, and automation solutions that solve real business problems. You'll work closely with business and technology teams to bring these solutions from concept to production, creating measurable impact across the organization.
Key Responsibilities
Design, develop, and deploy AI applications, from proof of concept through production.
Build ML, deep learning, and generative AI models to solve specific business problems.
Develop AI agents and intelligent workflow automations that orchestrate tools, APIs, and decision logic.
Integrate AI solutions with enterprise systems, applications, APIs, and data sources.
Partner with business stakeholders to translate requirements into technical solutions.
Evaluate, monitor, and optimize models and applications for performance, reliability, and scalability.
Document technical designs and contribute to AI development standards and best practices.
Track emerging AI technologies and recommend solutions aligned with business objectives.
Qualifications
Required
Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related field.
3-5 years of experience in AI, machine learning, agentic AI, and workflow automation.
Experience developing applications, APIs, and system integrations.
Strong analytical, problem-solving, and communication skills.
Ability to manage multiple initiatives and work effectively across cross-functional teams.
Knowledge of AI governance, security, and responsible AI practices.
Technical Skills
Languages & Core ML: Python, Machine Learning, Deep Learning, Generative AI
LLMs & Agentic AI: LLM Development, Prompt Engineering, RAG, AI Agent Frameworks (LangChain, LangGraph), Multi-Agent Orchestration, Fine-Tuning
ML/DL Frameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers
Microsoft Azure AI Stack: Azure OpenAI Service, Azure AI Studio, Azure Machine Learning, Azure AI Search, Azure Functions
Data & Retrieval: Vector Databases, Semantic Search, Embeddings, Data Pipelines
Integration & APIs: REST APIs, Webhooks, Enterprise System Integrations
DevOps & Deployment: Docker, Azure DevOps, Git, CI/CD, MLOps