[Hiring] Staff Architect @6sense

Role Description

We’re looking for a Staff Architect to lead architecture and technical delivery for a major domain within 6sense’s Revenue Intelligence platform (e.g., real-time signals ingestion & processing, ML inference/serving, multi-tenant data isolation, or GTM integrations & activation). This is a senior individual contributor role focused on high-leverage system design + execution leadership: driving architecture for complex initiatives, partnering closely with engineering and product leaders, and ensuring solutions are scalable, resilient, secure, and operable. You will be hands-on where it matters — through reference implementations, prototypes, and deep technical guidance that helps teams ship.

Key Responsibilities

• Domain Architecture Ownership
  • Own the architecture for a core domain of the platform, ensuring it meets scalability, reliability, security, and performance requirements.
  • Drive end-to-end design for cross-service initiatives: clarify requirements, propose options, lead tradeoffs, and align stakeholders.
  • Produce high-quality design artifacts (HLDs, LLDs, data flow diagrams, API contracts) and lead design reviews.
• Delivery Enablement (Hands-on Leadership)
  • Provide hands-on technical leadership through reference implementations, prototypes/POCs, and critical-path contributions when needed.
  • Partner with engineering teams to translate architecture into executable plans (milestones, risks, dependencies, rollout strategy).
  • Help teams build “operable” systems: instrumentation, alerting, runbooks, dashboards, and failure-mode thinking.
• Data & Signal Processing (if domain-aligned)
  • Lead architecture for ingestion/enrichment pipelines handling large-scale behavioral events and third-party data.
  • Drive improvements to data quality, lineage, observability, and freshness SLAs.
• AI/ML Serving (if domain-aligned)
  • Guide architecture for feature pipelines and inference serving (batch and online), model monitoring, experimentation, and safe rollouts.
  • Partner with data science and ML engineering to productionize reliable, scalable ML systems.
• Multi-Tenant & Platform Foundations (if domain-aligned)
  • Drive patterns for tenant isolation, tenant-aware configuration, partitioning strategy, and scalable onboarding.
  • Identify and mitigate risks around compliance, data integrity, and access control.
• Integration & Activation
  • Lead architecture for integrations with CRM/MAP/GTM tools (Salesforce, HubSpot, Marketo, Outreach, etc.).
  • Establish patterns for reliable data activation (idempotency, retries, backfills, versioning, and extensibility).
• Engineering Excellence & Mentorship
  • Raise the bar through design reviews, technical mentorship, and knowledge-sharing.
  • Contribute to architecture standards and reusable patterns; participate in architecture forums/councils.
  • Identify architectural risks early and drive mitigation plans.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8+ years in software engineering with significant focus on distributed systems and system design.
• Demonstrated experience designing and delivering data-intensive, distributed, cloud-based systems.
• Strong understanding of:
  • Distributed systems, reliability, scalability, fault tolerance.
  • Microservices/event-driven architectures.
  • API design, data modeling, integration patterns.
  • Observability and operability (metrics/logging/tracing, incident learnings).
• Experience with a major cloud platform (AWS, GCP, or Azure).
• Ability to influence across teams through clear communication, strong design rationale, and pragmatic decision-making.

Preferred Qualifications

• Experience in B2B SaaS, MarTech/AdTech/Revenue Tech, or similar data-heavy product environments.
• Experience with streaming/batch data systems (Kafka/Flink/Spark or equivalents).
• Familiarity with OLAP/analytics stores (ClickHouse/Redshift/BigQuery/Druid/Trino, etc.).
• Familiarity with ML platform concepts (feature pipelines, inference patterns, monitoring), even if not a full-time ML practitioner.
• Experience designing multi-tenant data and service architectures.

What Success Looks Like

• A well-defined domain architecture that enables teams to ship confidently and operate reliably in production.
• Reduced latency/freshness gaps, improved reliability/SLOs, and improved cost-to-serve within your domain.
• Faster onboarding of new data sources/integrations or faster rollout of new AI-driven capabilities (depending on domain).
• Strong cross-team alignment, fewer architectural surprises, and smoother delivery of major initiatives.

Benefits

• Health coverage.
• Paid parental leave.
• Generous paid time-off and holidays.
• Quarterly self-care days off.
• Stock options.
• Support for equipment and connectivity needs.
• Access to LinkedIn Learning platform for development initiatives.
• Quarterly wellness education sessions.