Senior Solutions Engineer

Engineering|New York City - Remote or Hybrid, 1 day/week if hybrid|Full-Time

Job Summary

We are looking for a technical owner of the customer journey from late stage sales meetings through pilot by running demos and solution scoping alongside Sales, standing up and integrating each pilot in the customer's cloud, and bug triage so the founders and core engineering team stay focused on closing and building.

About Us

Malachyte is building a frontier personalization engine that adapts the internet in real time — making every visitor feel understood from their very first click. Our founding team brings decades of deep expertise from roles at Spotify, Priceline, BCG, Google and more.

Malachyte's journey starts with e-commerce companies who rely on their websites to help consumers discover and satisfy their intent. Our innovative solutions are a blend of advanced infrastructure, deep learning, and next-gen user experience to deliver value within weeks.

Once set-up, our technology instantly personalizes every experience in real-time, making browsing and searching more relevant for every visitor from their first interaction (no login or history required!).

We're still in the early stages of company building - this role is for someone who wants outsized ownership of how our customers succeed.

Responsibility Pillars

Pre-sales solution engineering

Own technical demos and solution-architecture conversations so a founder no longer needs to be in every demo.
Scope POCs and pilots: translate the buyer's surfaces (search, PLP, recommendations) into a concrete deployment and success-measurement plan.
Run technical discovery and answer integration / security / data questions for engineering and IT stakeholders on the customer side.

Pilot onboarding & integration

Stand up the single-tenant deployment in the customer's cloud (GCP by default); integrate with enterprise data sources.
Implement event / clickstream instrumentation and confirm visitor-ID population, consistency, and event-payload completeness before any metric is committed, validating inputs.
Run the onboarding cadence: Day 0 access, Day 1 kickoff, Day 3 data check, Day 7 risk review with customer.
Own the measurement plumbing in the Pilot Success Brief: the A/B testing integrity and results from instrumentation to read out.

Customer optimization & support

Triage the customer bug queue: resolve config issues directly and route true product bugs to engineering with a clean reproduction.
Support technical adoption of new releases that require client-side changes (e.g. a new endpoint) working directly with the brand's technical team to implement as needed.
Surface deployment and field learnings to product (why we win, where integration hurts) feeding into, not replacing, existing roadmap prioritization.
Review and validate auto-generated onboarding runbooks and content for technical accuracy.

Requirements

Must-Haves

Strong Differentiators

3+ yrs as a Solutions / Sales Engineer, Forward-Deployed Engineer, or Implementation / CS Engineer at a B2B SaaS, data, or ML company.

E-commerce, personalization, search, or recommendations domain (Algolia / Bloomreach / Constructor / Coveo ecosystem, or recsys). NOTE: expect a different mental model.

Hands-on with cloud data infrastructure — GCP strongly preferred (BigQuery, Bigtable, GKE, Vertex AI, Managed Kafka).

Familiarity with Shopify's app/API ecosystem.

Comfortable with REST / JS-tag integration, event & clickstream instrumentation, and debugging data pipelines.

Has stood up customer environments across multiple clouds for enterprise deals.

SQL + light Python for independent data validation and tuning.

A/B testing & experimentation literacy — significance testing, Intelligems or similar.

Can run both a technical demo and a solution-architecture conversation — credible with a head of e-commerce / merchandising and with an engineering lead.

Experience writing customer-facing runbooks / help-center documentation.

High written-communication bar — writes a clean runbook and a clean bug reproduction.

Worked the Sept–Q4 peak-readiness cycle for a retail / e-commerce customer base.