Senior Infrastructure Developer

Job description

As a Software Engineer, you will design, implement, and operate multi-agent workflows that bring automation and intelligence to accelerate asset management.

What you get to do in this role

Design and build intelligent agent workflows that coordinate specialized AI agents through controlled orchestration frameworks. Engineer end-to-end multi-agent pipelines — from data retrieval and reasoning to evaluation and decision-making. Integrate frontier AI models (OpenAI, Gemini, Claude), or fine-tuned internal models for reasoning, enrichment, and contextual decision-making — select and switch models based on complexity, cost, and accuracy trade-offs.

Design, develop and maintain existing features, and enhance platform capabilities based on user feedback. Develop robust back-end services and APIs (Python or ServiceNow Scripting). Collaborate closely with SAM/HAM domain experts, product managers, and engineers to translate automation goals into resilient inbound agentic systems to deliver content at scale. Build intuitive UIs and dashboards in Service Portal, React, or Angular Leverage retrieval-augmented generation (RAG) strategies to ground AI reasoning in factual context from data sources — ensuring decisions are traceable and verifiable.

Apply observability, logging, and traceability across all agent workflows to ensure reproducibility, reliability, and continuous improvement. Participate in code reviews, post-deployment analysis, and production debugging to maintain system quality and stability at scale.

Qualifications

To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 6-8 years of software development experience with strong command on a any object oriented language Java/Python.

Hands-on experience developing LLM-powered or agent-based systems using frameworks for production use cases. Deep understanding of REST APIs, event-driven systems, asynchronous workflows, and back-end design. Experience implementing frontier AI models in enterprise workflow applications. Strong problem solving & foundation in data structures, algorithms, object-oriented design, and design patterns, with attention to performance and scalability.

Experience deploying AI or automation systems in production, emphasizing versioning, traceability, and performance monitoring. Familiarity with retrieval-augmented generation (RAG), vector stores, and prompt optimization. Working knowledge of the ServiceNow platform and JavaScript (ES6+) or willingness to learn these. Strong focus on code quality, observability, logging, and traceability — these are non-negotiable. Demonstrated ability to leverage or critically evaluate AI integration in work processes, decision-making, or problem-solving — including using AI-powered coding tools, automating workflows, analyzing AI-driven insights, and exploring AI's impact on business functions.