Intelligence Solution Engineer - Quality

Description

Key Responsibilities

• Integrate AI-driven pipelines with existing enterprise data ecosystems such as data warehouses, data lakes, and graph databases.
• Implement solutions leveraging frameworks like LangChain, LangGraph, and Databricks for scalable AI deployment.
• Design and maintain vector embedding databases, RAG (Retrieval Augmented Generation), and semantic retrieval systems for high-quality contextual understanding.
• Apply graph-based reasoning using Neo4j to enable contextual intelligence and knowledge discovery.
• Develop and optimize AI-driven applications using Python and Streamlit, ensuring seamless user interaction and robust functionality.
• Design and implement AI workflows leveraging Databricks ML and MLOps.
• Collaborate with stakeholders to build AI solutions, reducing redundancy and promoting standardization.
  

Responsibilities

Experience:

• 3–6 years of experience in Agentic AI solution engineering or intelligent systems development.
• Proven experience with LangChain , LangGraph , or equivalent agentic AI frameworks.
• Hands-on experience with Databricks , including Databricks ML and MLOps workflows.
• Strong expertise in Python and Streamlit for building interactive and intelligent applications.
• Experience integrating multimodal AI models and designing vector-based retrieval or RAG systems .
• Solid understanding of Neo4j or similar graph databases for context graph reasoning.
• Strong communication and collaboration skills for working with global, cross-functional teams.
  

Core Competencies

• Collaborates: Builds partnerships and works collaboratively with others to meet shared objectives.
• Communicates Effectively: Develops and delivers multi-mode communications tailored to diverse audiences.
• Customer Focus: Builds strong customer relationships and delivers customer-centric solutions.
• Interpersonal Savvy: Relates openly and comfortably with diverse groups of people.
• Data Analytics: Interprets and communicates complex data insights that drive business decisions.
• Data Mining: Extracts insights using advanced data exploration and visualization techniques.
• Data Modeling: Creates and validates data models using modern standards, ensuring compliance and accuracy.
• Data Communication & Visualization: Tells compelling data stories through visualizations and dashboards.
• Data Literacy: Understands and communicates data sources, methods, and applied techniques effectively.
• Data Profiling & Quality: Identifies and corrects data flaws, ensuring high-quality and reliable information.
• Values Differences: Recognizes and leverages the value that diverse perspectives and cultures bring.
  

Additional Information

• This position may require licensing or clearance for compliance with export control or sanctions regulations.
• Candidates must demonstrate both technical excellence and an applied understanding of AI-driven quality analytics.
  

Qualifications

Qualifications, Skills, and Experience:

Education

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related technical field.
• Equivalent experience may be considered.
  

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Relocation Package

100% On-Site