1196 وظيفة Substitute Front Desk Agent قريبًا مني

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Role summary

The Staff Software Engineer (IC4) on Sales and Order Management designs, builds, ships, and operates capabilities whose core behavior is model-driven rather than explicitly authored—agentic and conversational experiences that interpret a seller's or customer's intent, reason over catalog, quote, and order context, invoke tools, and act on the user's behalf across the quote-to-order lifecycle.

This is not a machine learning or AI research role; the engineer does not train foundation models. It is also distinct from traditional full-stack engineering, where systems follow deterministic logic rather than selecting execution paths at runtime. Two consequences shape the work. First, the most important logic often lives in natural language—instructions, prompts, tool descriptions, guardrails, escalation rules—which must be engineered, versioned, and reviewed with the same discipline as code. Second, because behavior is probabilistic, correctness is established by measuring behavior at scale rather than by asserting fixed outputs, making automated evaluation a first-class engineering activity rather than a quality-assurance afterthought.

The stakes in this domain sharpen both points. An agent operating on quotes and orders touches pricing integrity, contractual commitment, and revenue recognition—a confidently wrong output is not a bad answer, it is a mispriced order. At IC4 the engineer owns AI design decisions across the domain, not within a single feature, and owns the correctness of what ships whether a person or an agent produced it.

What you do Build AI-native capability across the order lifecycle

Design and ship features built around agentic behavior—intent interpretation, multi-step reasoning, tool invocation, and action on the user's behalf—together with the data models, integrations, and channels that make them usable in production. In Order Management this spans guided offer selection and configuration, natural-language order construction and validation, conversational order status and in-flight change, order-exception triage and resolution, and promise-date and availability inquiry.

Design AI-driven autonomous workflows

Decompose sales and order processes into the steps and decision points an agent can execute—determining where autonomy is appropriate, where a checkpoint with a person is required, and how exceptions, retries, and hand-back are handled. The design must make that distinction structural rather than advisory.

Author and maintain agentic instructions as engineering artifacts

Write, structure, and version the system instructions, role definitions, tool descriptions, guardrails, and escalation paths that govern agent behavior in the domain—under code review, source control, and regression coverage. Own the shared instruction and tool-description surface that adjacent teams build against.

Build automated evaluation and test non-deterministic behavior

Design and operate the evaluation that makes change safe — golden datasets, multi-turn conversation suites, model-as-judge scoring calibrated to human review, CI gates, and drift detection — plus adversarial, jailbreak, grounding, and tool-selection testing.

Design conversational experiences across channels

Build experiences that hold context across turns, hand off cleanly between automated and live agents, and behave consistently across chat and voice—accounting for what voice imposes: latency budgets, barge-in, speech recognition error, disambiguation, and explicit confirmation before consequential actions.

Specify precisely and direct AI coding agents

Convert requirements into testable specifications with explicit scope, constraints, non-goals, and acceptance criteria; decompose work into agent-sized tasks; supervise several workstreams in parallel; and review agent output for correctness, spec adherence, security, and maintainability. You own the result regardless of what produced it.

Own quality, safety, and reliability in production

Monitor conversation quality, containment, hallucination rate, tool-selection error, and unsafe or unauthorized action. Defend against prompt injection and data leakage across integration surfaces. Maintain reasoning-trace observability and model rollback mechanisms, and feed production failures back into specifications and evaluation sets. Lead root-cause analysis when agentic behavior deviates from intent.

Ground it in solid full-stack delivery

Build the application, APIs, data models, and integrations around these capabilities—front-end experiences for sellers and order agents, server-side logic, and the connections to quoting, billing, contract, case, and fulfillment systems—with the CI/CD, observability, and upgrade-safe extensibility expected of production software.

Collaborate across product, design, and engineering

Partner with product managers, designers, conversation designers, and engineers to define success criteria and communicate capability and risk clearly. Mentor IC1 to IC3 engineers, and raise the team's practices around instruction authoring, evaluation, and accountable agent use.

Required experience and skills

• Production track record. A demonstrated record of building, shipping, and operating production software, including hands-on delivery of AI-native application features that real users depend on rather than demos or prototypes. Depth and demonstrated judgment matter more than tenure; typically around 8+ years of relevant software engineering experience.
• Agentic delivery experience. Direct experience authoring agentic instructions and prompts, designing AI-driven autonomous workflows, and building the evaluation and testing that verifies them. This is required, not preferred.
• Production AI integration. Experience integrating large language model APIs and retrieval-grounded features, including agent orchestration, tool and function calling, and structured output enforcement.
• Domain ownership. Demonstrated ownership of a complex domain or subsystem end-to-end, including the architectural decisions, migrations, and operational consequences.
• Engineering fundamentals. Strong command of data structures, algorithms, system design, APIs, data modeling, and testing. Proficiency in front-end development with a modern component framework, server-side development, relational data modeling, and REST and GraphQL API design.
• Applied machine learning literacy. A working command of the concepts that govern how these systems behave—evaluation, embeddings, and the probabilistic output and failure modes of modern models—sufficient to reason about, debug, and verify model-driven behavior in production.
• Accountable use of AI coding agents. Current, effective use of AI coding assistants and agents with evidence of accountable delivery: precise specification, critical review of generated output, and verification harnesses.
• Operational experience. Hands-on CI/CD, containerized workloads, and observability experience, plus direct on-call and incident-command experience with customer-facing systems.
• Mentorship. Demonstrated mentorship of less-experienced engineers and a record of raising quality through code review.
• Education. Bachelor's degree in computer science, software engineering, or a related technical field, or equivalent practical experience. Advanced degrees are a plus but not a substitute for a record of shipping reliable AI-native applications.

Preferred experience

• 
  Order and quoting domain depth. Quote-to-cash, configure-price-quote, product catalog modeling, or order management, at a depth sufficient to challenge a requirement rather than only implement it.
• Evaluation and observability tooling. Evaluation frameworks, prompt and instruction management tooling, tracing for model-driven applications, and analysis of production transcripts at scale.
• Conversation design partnership. Working alongside conversation or content designers on dialogue flow, tone, and error-recovery design.
• Forward deployed delivery. Building against a customer's data, integrations, and channels, and tuning instructions and evaluation sets in their environment.
• Platform and standards depth. Industry order-management interoperability models, or Now Platform development experience: scoped applications, Flow Designer, UI Builder, Automated Test Framework, and upgrade-safe extension patterns.

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.

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