Role Overview We are seeking an AI Engineer to design, build, and scale AI-powered solutions across the enterprise. This role sits within the AI Engineering function and is responsible for translating business needs into production-grade AI systems, with a primary focus on LLM-based solutions (e.g., ChatGPT/OpenAI) while maintaining flexibility to integrate emerging AI platforms. You will work closely with AI Enablement, IT, and business stakeholders to deliver secure, scalable, and high-impact AI capabilities that improve productivity and drive measurable business outcomes. Key Responsibilities AI Solution Development & Engineering Design and implement AI-powered workflows and applications using LLMs (ChatGPT/OpenAI, and future platforms) Build and maintain agent-based systems, orchestration layers, and prompt frameworks Develop APIs and services to integrate AI into enterprise systems (e.g., ServiceNow, internal tools, data platforms) Implement RAG (Retrieval-Augmented Generation) architectures using enterprise data sources Ensure solutions are modular, reusable, and scalable AI Architecture & Integration Define and implement AI system architecture , including model selection, routing, and orchestration Integrate AI capabilities into existing enterprise ecosystems Partner with security and data teams to enforce: Data boundaries Access controls Compliance requirements Prompt Engineering & Optimization Develop and maintain enterprise prompt libraries and reusable frameworks Optimize prompts and agent flows for: Accuracy Consistency Cost efficiency Collaborate with AI Enablement to standardize prompt patterns across teams Evaluation & Performance Improvement Design and execute evaluation frameworks (e.g., OpenAI Evals, DeepEval) Build automated pipelines to test: Accuracy Reliability Edge-case handling Continuously monitor and improve model performance in production AI Use Case Enablement Partner with business stakeholders to: Identify high-value AI use cases Translate requirements into technical solutions Rapidly prototype and iterate on AI solutions Required Qualifications Education & Experience Bachelor’s degree in Computer Science, Computer Engineering, or related field 1–5+ years of experience in software engineering or AI/ML engineering (flexible based on capability) Hands-on experience building AI/LLM-based applications Technical Skills Programming: Python (required), JavaScript/TypeScript (preferred) Frameworks & Tools: LLM tooling: OpenAI APIs, LangChain/LangGraph, Flowise (or similar) Backend: FastAPI, Node.js Frontend (nice to have): React Data & AI: Pandas, NumPy, basic ML concepts Experience with RAG pipelines and vector databases DevOps & Engineering: Git/GitHub API design and integration Containerization (Docker preferred) AI-Specific Experience Experience building AI agents, chatflows, or automation workflows Familiarity with evaluation frameworks and testing methodologies Understanding of prompt engineering and LLM behavior Preferred Qualifications Experience integrating AI into enterprise environments Exposure to ServiceNow, ITSM workflows, or enterprise support systems Knowledge of data pipelines and knowledge management systems Familiarity with AI governance, security, and compliance considerations Experience working in Agile/Scrum environments Soft Skills Strong problem-solving and systems thinking Ability to translate ambiguous business problems into technical solutions Effective communication with both technical and non-technical stakeholders Proactive, adaptable, and able to operate in a fast-evolving AI landscape