Forward Deployed Solution Architect
18 hours ago
Why This Role Matters
Enterprise leaders aren't just experimenting with AI-they're demanding outcomes. The next wave of adoption will be led by those who can move fast, deliver measurable value, and transform 1-off wins into repeatable success.
As a Forward Deployed Solution Architect (FDSA), you operate on the frontlines of that transformation. You embed with customers to uncover opportunities, architect AI-powered systems that drive ROI, and guide how those solutions scale across the Now Platform.
This is a rare opportunity to serve as a field product architect at the forefront of applied AI, helping define what great looks like for scalable enterprise innovation
Job Description:
What you get to do in this role
You are a dynamic and innovative problem-solver who thrives in complex, fast-paced environments. With a strong analytical mindset and a passion for AI, you excel at transforming ambiguity into clarity. Your ability to synthesize data, workflows, and user motivations allows you to identify impactful solutions that align with customer needs and business objectives.
You work seamlessly with software engineers, product designers, and stakeholders to deliver intelligent systems that address mission-critical challenges. You dive deep into complex environments to explore workflows, understand user friction, and surface the right inflection points for intelligent automation.
You embody ServiceNow's values: - Customer First : You prioritize delivering value through business outcomes. - Bold Innovation : You challenge convention and seek simplicity through design. - One Team : You collaborate deeply across functions and build through shared ownership. - Integrity and Belonging : You build trust, foster inclusion, and lead with empathy.
- Lead Strategic Discovery : Identify high-impact AI opportunities by running hands-on workshops and aligning stakeholders.
- Architect AI-Native Solutions : Design systems using LLMs, RAG pipelines, retrieval logic, and workflow orchestration.
- Accelerate Delivery with Engineers : Collaborate closely with FDSEs to build, test, and iterate functional solutions quickly.
- Codify Best Practices : Create repeatable frameworks, reusable templates, and modular components.
- Drive Alignment : Influence customer and executive buy-in through clear storytelling and solution framing.
- Advocate Field Insights : Capture feedback from deployments to shape product strategy and prioritize platform needs.
- Enable Scale : Equip internal teams and customers to expand success through documentation and technical onboarding assets.
Qualifications:
What You Bring
- Enterprise Experience : 15+ years of overall experience, with 5-7+ years in enterprise AI/ML architecture, field engineering, or solution consulting. Proven ability to lead initiatives from conception to delivery over at least 3+ years.
- Technical Mastery : Strong grasp of LLM-based systems and GenAI pipelines including prompt engineering, retrieval-augmented generation (RAG), orchestration, and data modeling. Experience designing full-stack intelligent workflows.
- Cloud & Infrastructure Fluency : Deep hands-on experience with AWS, Azure, or GCP, including use of containers, infrastructure-as-code (Terraform, CloudFormation), and enterprise integration patterns.
- Engineering Depth : Proficient in Python and SQL, with working knowledge of GenAI tooling frameworks like LangChain, Semantic Kernel, or similar. Ability to contribute to engineering discussions and code-level decisions.
- Customer & Delivery Leadership : Comfortable operating in ambiguous, high-stakes environments. Experienced in guiding cross-functional technical teams, influencing executive stakeholders, and ensuring clarity from ideation to implementation.
- Field Readiness : Willingness and ability to travel up to 30% to embed onsite with customers, lead workshops, unblock teams, and drive tangible solution outcomes.
- Platform Affinity (Nice to Have) : Familiarity with the ServiceNow platform, low-code tooling, or other enterprise SaaS ecosystems.
Preferred Qualifications
- Prior work delivering AI or intelligent workflow solutions at scale.
- Familiarity with LangChain, Semantic Kernel, vector DBs, and Python.
- Experience with SaaS platforms, enterprise data integration, and low-code environments.
- History of converting field delivery into reusable product patterns.
- Proven success in deploying AI solutions that delivered tangible customer impact.
- Hands-on experience integrating AI into enterprise SaaS platforms.
- Skill translating real-world constraints into reusable internal tools or product enhancements.
- Familiarity with AI governance, compliance, and enterprise security practices.
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