AI Engineering

Implement Agentic AI systems leveraging frameworks such as LangChain, Google ADK, Strands, and Semantic Kernel.

Apply advanced prompt engineering techniques to improve accuracy and robustness of LLM systems.

Build multimodal AI solutions, integrating text with images or structured data to support enterprise use cases.

Apply harness engineering practices to systematically design, test, and evaluate AI workflows.

Develop reusable agent tooling and integrations, including Model Context Protocol and Agent-to-Agent communication.

Collaborate with stakeholders to translate business problems into scalable GenAI-driven solutions.

Leverage modern AI developer tooling such as Claude CLI, GitHub Copilot, and Vertex AI.

• Support deployment and operationalization of AI solutions using AWS and GCP clouds.