Agentic AI Developer

Company Description

About Sutherland

Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise.

We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence.

We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model.

For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships.
Sutherland

Unlocking digital performance. Delivering measurable results.
 

Job Description

We are seeking an Agentic AI Developer to build intelligent, autonomous AI systems that can reason, retrieve knowledge, and act across multiple tools and data sources. The role focuses on developing multi-agent pipelines, RAG systems, and real-time AI-driven applications.

Responsibilities

• Design and develop agentic AI systems using LLMs, tools, and orchestration frameworks.
• Build RAG pipelines for structured and unstructured data.
• Implement multi-agent workflows for document understanding, OCR, and data extraction.
• Build APIs and services using Python and FastAPI for AI pipelines. 
• Evaluate and improve model accuracy, latency, and reliability

Qualifications

Required Skills

• Strong proficiency in Python and SQL.
• Experience with LLMs, RAG, and multi-agent systems.
• Hands-on with LangChain, LangGraph or similar frameworks.
• Experience with vector databases and OCR tools.
• Experience deploying models on cloud platforms (Azure preferred).
• Knowledge of prompt engineering and agent reasoning patterns.
• Familiarity with cloud deployment and Docker.

Good to Have

• Exposure to cloud platforms (GCP) .
• Exposure to MLOps experience.
• Knowledge of CI/CD tools.

Additional Information

All your information will be kept confidential according to EEO guidelines.