Pega Developer

Cloudious•Dallas, TX

About The Position

Seeking a highly skilled Senior Automation and AI Solutions Architect with hands-on experience in Camunda 8, automation development, and AI integration. The role designs and develops enterprise-grade automation solutions, integrates AI technologies, and collaborates with business teams to improve operational efficiency through automation strategies. The posting states experience required of 10+ years with Agentic AI and PEGA. The role is based in Dallas, Texas, for a duration of 12+ months. The successful candidate will contribute substantial experience in automation and AI, a passion for innovation, and a commitment to delivering high-quality solutions that support business success. The role is described as critical to transforming the automation landscape and enhancing operational capabilities.

Requirements

10+ years of experience with Agentic AI and PEGA.
Strong hands-on experience with Camunda 8, including BPMN, DMN, and Zeebe.
Proficiency in Python for automation development.
Experience integrating AI, specifically large language models and Agentic AI frameworks.
Solid understanding of RPA platforms, including UiPath, Testing Anywhere, and Microsoft Power Automate.
Experience with integration and APIs for enterprise applications.

Nice To Haves

Familiarity with Intelligent Document Processing and knowledge automation solutions.
Experience developing monitoring and observability solutions.
Knowledge of Identity and Access Governance and compliance standards.
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.

Responsibilities

Design and develop enterprise-grade automation solutions using Python for unattended and attended workflows.
Build reusable automation frameworks and accelerators to streamline development.
Integrate automation solutions with enterprise applications through APIs and convert manual business processes into scalable automated solutions.
Design and implement AI agents for autonomous task execution, including multi-agent workflows using Agentic AI frameworks.
Develop AI-powered decision engines for exception handling and implement Human-in-the-Loop controls for business-critical workflows.
Collaborate with business teams to identify opportunities for Agentic AI implementation.
Integrate OpenAI, Azure OpenAI, Claude, Gemini, or equivalent large language models into existing systems.
Develop Retrieval-Augmented Generation solutions and implement prompt engineering and evaluation mechanisms.
Build intelligent document processing and knowledge automation solutions while ensuring AI governance, observability, and responsible AI compliance.
Use RPA platforms such as UiPath, Automation Anywhere, or Power Automate to develop API-based integrations with enterprise applications.
Implement monitoring, logging, alerting, and observability mechanisms for production deployments and automation maintenance.