AI Engineer

AI Solution Development
Design, develop, deploy, and maintain AI/ML and Generative AI solutions using Python.
Build and integrate LLM-powered applications using frameworks such as LangChain and model APIs including OpenAI and Anthropic.
Develop AI solutions from proof of concept through production deployment.
Implement RAG architectures, embeddings, semantic search, caching, prompt engineering, and tool/function-calling capabilities.
Create evaluation frameworks and testing methodologies for AI applications.
Software Engineering & Integration
Develop robust APIs, orchestration layers, and microservices supporting AI workloads.
Design logging, monitoring, observability, and performance-tracking mechanisms for AI systems.
Implement scalable and maintainable software engineering practices for AI products.
Collaborate with development teams to embed AI capabilities within enterprise applications.
Data Engineering & Analytics
Process, transform, and analyze structured and unstructured data from various enterprise systems.
Utilize Python libraries such as NumPy, Pandas, and Polars for advanced data manipulation.
Develop and optimize SQL queries for large-scale relational databases.
Extract business value from complex and disconnected datasets.
Platform & Ecosystem Enablement
Identify recurring business and technical requirements across Data & AI initiatives.
Develop reusable frameworks, standards, governance models, and best practices.
Contribute to the evolution of enterprise AI capabilities, services, and operating models.
Promote AI adoption and knowledge sharing across cross-functional teams.
DevOps & Cloud Engineering
Work within Agile and DevOps delivery models.
Support CI/CD implementation through Azure DevOps and GitHub.
Build and maintain cloud-native AI solutions on Microsoft Azure.
Collaborate with platform, architecture, and security teams to ensure scalable and compliant deployments.