Sr Software Engineer

Role Overview

Leadership Responsibilities

• Manage daily tasks, mentor engineers, review code and AI behavior, evaluate performance, and track quarterly goals.
• Assist with training and recruitment, provide leadership updates, and support root cause analysis for customer-reported issues.
• Collaborate with product management, domain specialists, and engineering to define requirements and scalable AI-driven solutions.
• Stay current with AI models, frameworks, techniques, and opportunities to apply them to products and services.

Software Development

• Develop AI-native software and technical specifications covering model selection, prompt and agent design, and data or retrieval architecture.
• Automate tests and build evaluation harnesses for accuracy, regression, and hallucination checks.
• Troubleshoot coding and model-behavior problems and maintain software updates for customer and company concerns.
• Apply prompt-injection defenses, data privacy, PII handling, and responsible-AI guardrails.
• Use IaaS practices and managed AI/ML services; Kubernetes, containerization, model serving, and GPU deployment are welcome or advantageous.

Communication

• Communicate with internal and external customers and liaise with team members, management, and clients.
• Explain AI capabilities, trade-offs, limitations, and non-deterministic behavior through presentations and progress reports.
• Identify opportunities to improve business software processes through AI and automation.

Technical Qualifications

• 5-8 years of practical Java experience and 3-5 years of prompt engineering and prompt or agent scripting experience.
• 3-5 years integrating third-party AI/ML services and platform APIs.
• Proficiency in Python, Java, and JavaScript, with strong Python skills for ML and AI development.
• Experience with domain-specific languages, prompt templates, agent instruction frameworks, microservices, and embedding pipelines.
• Experience with RESTful and streaming APIs, model endpoints, web services, JSON, SQL, and NoSQL or vector stores.
• Knowledge of cloud computing and managed AI services such as AWS Bedrock, SageMaker, Azure OpenAI, or Google Vertex AI.
• Experience with RAG assistants, agentic workflows, AI-driven customer service, and data or knowledge-base migration tools.
• Experience with LLM orchestration, retrieval frameworks, vector databases, Spring Boot or similar frameworks, and Agile or Scrum.

Additional Qualifications

• Strong collaboration, communication, problem-solving, debugging, independent working, and learning abilities.
• Ability to develop unit tests and AI evaluation harnesses and isolate root causes in probabilistic and distributed systems.
• Bachelor's degree in computer science or a related field; ML or AI coursework or experience is a plus.

Work Arrangement

• ServiceNow describes work personas as flexible, remote, or required in office depending on the nature of the work and assigned location.
• The description does not explicitly establish a specific onsite, remote, or hybrid arrangement for this role.

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