Why This Role Stands Out
This AI Scientist role offers an exciting opportunity to design and build cutting-edge agentic AI systems and RAG pipelines, leveraging modern frameworks and deploying on Google Vertex AI. You'll thrive here if you're a mid-senior professional passionate about advanced AI development, clean code, and collaborative engineering practices, with the flexibility of a hybrid work environment. Apply now to shape the future of AI at MHK TECH INC!
Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Dallas, TX, United States
Posted
6 weeks ago
DockerFastAPILLMPython
Job Description
Agentic AI & Orchestration:
- Design and build multi-agent systems for data workflows agents that retrieve, generate, validate, and iterate autonomously
- Implement agent orchestration using frameworks such as Google ADK, LangGraph, or LangChain
- Deploy and manage agents on Google Vertex AI
Document Understanding & RAG:
- Build document processing pipelines (PDFs, Word/DOCX) extraction, parsing, table detection, structure recognition
- Design and build RAG pipelines grounded in source documents
- Process, extract and transform data from unstructured and semi-structured sources
Code Quality & Engineering Practices:
- Write clean, well-tested, maintainable Python code following SOLID principles and recognised design patterns
- Apply single responsibility, dependency inversion, and interface segregation in real codebases not just theory
- Write meaningful tests, and maintain high standards across the team
- Refactor and improve existing code as part of normal development workflow
AI-Assisted Development:
- Use AI coding tools (e.g.Gemini CLI, GitHub Copilot) as a core part of your development workflow
- Critically review and validate AI-generated code understanding what it produces, why, and when it s wrong
- Write effective prompts to direct AI tools toward correct, secure, well-structured output
- Know when to use AI and when to write code manually judgement over speed
Platform & Infrastructure:
- Integrate and orchestrate LLM providers available through Google Vertex AI (Gemini, etc.)
- Build internal tools and applications using Streamlit and FastAPI
- Containerize and deploy services using Docker
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