Design, build, and deploy AI-powered applications and services that integrate with existing systems and workflows.
Prototype and iterate on AI solutions rapidly, translating business needs into functional AI features within short development cycles.
Develop and implement agentic AI workflows (e.g., planning, reflection, tool use) using modern orchestration frameworks such as LangGraph.
Apply prompt engineering and retrieval-augmented generation (RAG) techniques to improve model accuracy, reliability, and performance.
Prepare and manage multimodal datasets by cleaning, transforming, and structuring complex data sources including documents, PDFs, and images.
Stay current with the evolving AI ecosystem—evaluating new models, benchmarking performance, and selecting the right tools for each use case.

Requirements

Proven experience building, deploying, and maintaining AI-powered solutions in production environments.
Strong understanding of modern AI/LLM ecosystems, including model evaluation, benchmarking, and selecting models for specific tasks.
Experience implementing agentic workflows (e.g., planning, reflection, tool use) and orchestration frameworks such as LangGraph or similar systems.
Proficiency with web application development using Next.js, React, and Python backend frameworks such as FastAPI or Flask.
Experience with prompt engineering, retrieval-augmented generation (RAG), and integrating AI capabilities via REST APIs.
Familiarity with cloud infrastructure (AWS preferred), Databricks, Oracle ERP and agentic AI frameworks.
Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced, agile environment.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI-powered applicationsagentic AI workflowsprompt engineeringretrieval-augmented generationweb application developmentNext.jsReactPythonFastAPIFlask

Soft Skills

communicationcollaborationagile environment