Agentic AI Engineer

Innova Solutions•Charlotte, NC

1d•Onsite

About The Position

As an Agentic AI Engineer, you will be responsible for designing, coding, testing, debugging, and documenting applications and services, including upgrades and deployments. You will review technical challenges that require in-depth evaluation of technologies, procedures, and engineering approaches. You will resolve moderately complex issues while guiding teams to meet existing and emerging business needs. You will collaborate with peers, colleagues, and mid-level managers to resolve technical challenges and meet project goals. You will lead projects and act as an escalation point, providing direction to less experienced engineers. You will design, develop, and deploy AI applications using enterprise APIs, LLMs, agent frameworks, and related technologies. You will implement prompt engineering, retrieval augmented generation, fine-tuning, and agentic design patterns. You will integrate LLM models with existing enterprise systems and ensure that AI solutions meet governance, security, and compliance standards. You will troubleshoot complex application and model-related issues and contribute to the continuous improvement of AI systems. You will assist and mentor engineers in advanced software development and AI engineering practices. You will stay informed of advancements in AI, LLMs, and agent frameworks and apply relevant updates to products and systems.

Requirements

Experience in agentic automated applications and Agentic Engineering.
Microsoft Power Platform (Power Apps Power Automate, PVA, Power BI), UI Path
AI SDLC experience (DEVI AI, Claude Code, Claude Design), Lang chain (or any other Agentic framework)
Alteryx (Data transformation and automation), IDP (intelligent document processing), Microsoft Co-Pilot Studio
Agentic AI (Hands on experience on Gitogenin/Vertex AI)
Experience in software engineering experience or equivalent through a combination of work experience, training, military service and Generative AI, large language models, or foundation models.
Experience with either GCP, Azure, Kubernetes, or OpenShift and Python.
Experience with REST API development and containerization technologies such as Docker and Kubernetes.
Experience using Git for source code version control, including branching, pull requests, and collaborative development workflows.

Responsibilities

Design, code, test, debug, and document applications and services including upgrades and deployments.
Review technical challenges that require in depth evaluation of technologies, procedures, and engineering approaches.
Resolve moderately complex issues while guiding teams to meet existing and emerging business needs.
Collaborate with peers, colleagues, and mid-level managers to resolve technical challenges and meet project goals.
Lead projects and act as an escalation point, providing direction to less experienced engineers.
Design, develop, and deploy AI applications using enterprise APIs, LLMs, agent frameworks, and related technologies.
Implement prompt engineering, retrieval augmented generation, fine tuning, and agentic design patterns.
Integrate LLM models with existing enterprise systems and ensure that AI solutions meet governance, security, and compliance standards.
Troubleshoot complex application and model related issues and contribute to the continuous improvement of AI systems.
Assist and mentor engineers in advanced software development and AI engineering practices.
Stay informed of advancements in AI, LLMs, and agent frameworks and apply relevant updates to products and systems.