The AI Agent Engineer joins the software and core IT team to design, build, and scale enterprise integrations and data pipelines. This role focuses on connecting Serval integrations, SaaS platforms, and enterprise AI tools with core business systems through secure, reusable patterns. You will build robust integrations using APIs, webhooks, scripts, middleware, and orchestration logic while modernizing legacy interfaces into event-based patterns. Key responsibilities include designing LLM prompts, developing context strategies, and managing grounding approaches for AI-enabled processes. You must utilize Python, Git, and REST APIs to ensure reliable data flow and platform interoperability. The work involves solving complex connectivity needs, managing data transformations, and ensuring security compliance across multi-system environments to support large-scale enterprise transformation and workflow continuity.
Design, build, and maintain robust integrations using APIs, webhooks, scripts, and middleware services.
Develop reusable integration templates, services, and accelerators to standardize connectivity across the enterprise.
Design and refine prompts for large language models to support enterprise workflows and AI-enabled processes.
Integrate LLM capabilities with enterprise applications, data sources, and identity services while ensuring security and privacy.
Modernize legacy interfaces into scalable, API-driven, and event-based integration patterns.
Define source-to-destination data mappings, transformation logic, and exception-handling patterns for reliable data flow.
Create coexistence models to allow legacy and modern platforms to interoperate during phased system transformations.
Author technical designs, dependency maps, and operational runbooks to support long-term sustainment of integrated solutions.
What we're looking for
7+ years of hands-on experience in integration engineering, systems engineering, software engineering, platform architecture, or enterprise application integration.
Bachelor’s degree in Computer Science, Information Technology, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
Production-level proficiency in Python and core scripting or automation frameworks.
Extensive experience building enterprise-grade integrations using REST APIs, webhooks, middleware, event-driven services, and ETL logic.
Extensive hands-on experience prompting large language models for business, technical, or automation use cases.
Experience integrating LLMs with enterprise applications, APIs, data sources, and workflow orchestration components.
Strong foundational knowledge of enterprise authentication, authorization, identity integration, and secure API practices.
Relevant cloud, integration, systems engineering, cybersecurity, or AI certifications (preferred).