AI Engineer - Mid-Level

KRDL USA is seeking a hands‑on AI Engineer to develop and integrate AI solutions for a client engagement. This role involves Python, large language model (
LLM
) applications, AI agents, Model Context Protocol (
MCP
) servers, API integrations, cloud technologies, and Cisco Webex Contact Center
.

The ideal candidate will have experience building AI applications and Webex AI agents, connecting enterprise systems, and delivering reliable solutions that improve business workflows and customer interactions.

This is a mid-level individual contributor role with opportunities to collaborate with technical leaders, architects, and business stakeholders.

Experience with Retrieval-Augmented Generation (
RAG
) and AI solution architecture is a strong plus.

Location:

Lincolnshire, IL
Work Arrangement:
To be confirmed

Employment Type:

Full Time / Client Consulting Assignment

• Design, develop, and deploy machine learning models and AI-driven applications
• Collaborate with cross-functional teams to define AI/ML requirements and deliver scalable solutions
• Build and maintain data pipelines to support model training, evaluation, and deployment
• Monitor and optimize model performance, accuracy, and efficiency in production environments
• Research and implement state-of-the-art AI/ML techniques and frameworks
• Contribute to code reviews, documentation, and engineering best practices
• Participate in agile development cycles and sprint planning

• Develop, test, and maintain AI applications using Python and LLM APIs.
• Build conversational assistants, document analysis solutions, knowledge retrieval capabilities, and workflow automation.
• Design and refine prompts, structured outputs, context management, and model interactions.
• Evaluate implementation options based on response quality, latency, security, and cost.

• Build, configure, test, and enhance AI agents for Cisco Webex Contact Center.
• Develop conversational flows that support customer self-service and defined business use cases.
• Integrate Webex AI agents with enterprise APIs, business applications, and knowledge sources.
• Implement escalation and handoff to human agents, preserving relevant interaction context.
• Collaborate with contact center stakeholders to clarify routing, workflow, and customer experience requirements.
• Test conversational behavior, integration reliability, fallback handling, and end-to-end customer journeys.
• Monitor interactions and recommend improvements to response quality and task completion.

• Build AI agents that use approved tools and APIs to complete defined tasks.
• Implement tool calling, workflow orchestration, state management, and appropriate human approval steps.
• Develop or integrate MCP servers that expose authorized tools, resources, and enterprise services to AI applications.
• Implement authentication, authorization, input validation, error handling, and logging.
• Test tool permissions, agent behavior, and recovery from failures.

• Develop document ingestion, extraction, cleaning, chunking, and embedding workflows.
• Integrate vector databases or search platforms to support semantic retrieval.
• Improve retrieval relevance, source attribution, and response groundedness.
• Connect AI applications to structured and unstructured data sources while respecting access permissions.

• Build and consume REST APIs using frameworks such as FastAPI or Flask.
• Integrate AI services with enterprise applications, databases, and third-party platforms.
• Deploy and support applications using approved Azure, AWS, or Google Cloud services.
• Contribute to containerization, CI/CD pipelines,…