Solutions Architect - US East Region

Nebuly; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Nebuly seeks a Senior Solutions Architect to bridge pre-sales and post-sales, convincing technically skeptical enterprise teams that Nebuly will work in their environment while ensuring value and deployment success.

You’ll close pilots and drive revenue expansion by understanding customers' AI stacks, data infrastructure, and security requirements in cloud or on‑prem environments.

Qualifications

• 5+ years in a Solution Architect, Sales Engineer, Solutions Engineer, or TAM role in a B2B SaaS environment.
• Excellent communicator with ability to translate complex tech for CIOs and DevOps.
• Strong commercial instinct—link tech success to revenue and expansion.

Responsibilities

• Pre-sales: partner with Sales Directors to win complex enterprise deals.
• Lead technical discovery of AI stack, data infrastructure, security, and deployment constraints.
• Design integration and deployment architectures (cloud or on-premise).
• Run pilots end-to-end from setup to weekly touchpoints and value demos.
• Build a technical business case to convert pilots into contracts.
• Post-sales: own the technical relationship after signature; be the primary contact for product or infra.
• Monitor adoption, identify risks, drive usage and value realization.
• Identify and develop expansion opportunities with Sales.
• Provide customer insights back to engineering and PM teams.

Skills

B2B SaaS

Strong communication

Commercial instinct

Technical storytelling

Tools

Datadog

Dynatrace

Splunk

New Relic

Job description

Location: US East Region – Remote

Type: Full-time

Level: Senior

Reporting to: Solutions Lead

About Nebuly

Nebuly is a fast-growing, VC-backed startup building the platform that proves the ROI of enterprise AI.

Every enterprise function — sales, customer support, HR, finance — is deploying AI agents at scale, and budgets are following fast. But most companies can’t answer a basic question: is this spend actually working? Every enterprise deploying AI agents is asking the same question: is this actually delivering value? Today, almost none of them can answer it. The signal that could answer it is right there — millions of conversations happening every day between employees, customers, and these agents — but it’s unstructured, high-volume, and invisible without the right infrastructure. So the ROI question stays unanswered, not because the answer doesn’t exist, but because no one can see it. Nebuly makes that signal visible. It sits on top of any enterprise AI deployment, turns those conversations into a clear answer — is this working, and where — and connects the dots back to ROI. Think of it as the accountability layer for enterprise AI: connect once, see the impact, prove the value — with no data ever leaving your environment.

Every new data category has created a new software category. CRM turned customer interactions into pipeline accountability. Product analytics turned user behavior into growth accountability. Nebuly is building that same layer for AI — turning millions of invisible conversations into a clear answer on value.

Our customers include Oura, CNH Industrial, Vodafone, and Moncler. Demand is accelerating fast, and we’re building the team to match.

Why This Role Matters

Closing an enterprise pilot is hard. Turning a pilot into a long-term, expanding contract is harder - and it is where this role lives.

As Solutions Architect, you sit at the intersection of pre-sales and post-sales. You are the person who convinces a technically skeptical enterprise team that Nebuly will work in their environment. You are also the person who makes sure it actually does - and that the customer gets enough value to expand.

Our product is technically complex. It plugs into enterprise AI infrastructure, handles sensitive conversational data, and often deploys on-premise inside a customer’s cloud. The person in this role needs to understand that environment deeply - and earn the trust of the engineers on the other side of the table.

This is not a support role. You are a technical closer and a customer success driver - directly responsible for pilot conversion and revenue expansion.

What You’ll Do

Pre-sales

• Partner with Sales Directors to win technically complex enterprise deals
• Lead technical discovery: understand the customer’s AI stack, data infrastructure, security requirements, and deployment constraints
• Design the integration and deployment architecture for each customer environment (cloud or on-premise)
• Run and manage pilots end-to-end - from technical setup to weekly touchpoints to demonstrating value
• Build the technical business case that converts a pilot into a signed contract

Post-sales

• Own the technical relationship with customers after signature - you are their primary point of contact for anything product or infrastructure related
• Monitor adoption, identify risks early, and work proactively with the customer to drive usage and value realization
• Identify and develop expansion opportunities in collaboration with the Sales team
• Feed customer insights and product gaps back to the engineering and PM teams

Who You Are

• 5+ years of experience in a Solution Architect, Sales Engineer, Solutions Engineer, or Technical Account Manager role in a B2B SaaS environment
• Deep familiarity with enterprise observability, monitoring, or analytics infrastructure - background at or with companies like Datadog, Dynatrace, Splunk, New Relic, or similar is a strong signal
• Experience with enterprise AI or data infrastructure is a plus
• Comfortable designing and discussing cloud and on-premise deployment architectures with senior technical stakeholders
• Strong commercial instinct - you understand the link between technical success and revenue, and you act on it
• Excellent communicator: you can translate complex technical concepts for a CIO and dig into infrastructure details with a DevOps team in the same day

Bonus Points

• Experience working with self-hosted or air-gapped enterprise deployments
• Background in LLM infrastructure, AI observability, or data pipelines
• Experience in a startup or early-stage environment where you had to build process from scratch

What We Offer

• Compensation is flexible and will be determined based on the candidate’s experience and overall fit with the company

We’re looking for someone who has done this before and is ready to do it again, at the right moment, in the right market.