Join a technology-driven team building the next generation of AI-powered marketing infrastructure. In this role, you will strengthen and evolve the systems that support complex marketing operations, lead management, and data governance.
Responsibilities
Design, build, and operate the next generation of marketing technology while ensuring existing systems remain reliable throughout the transition.
Develop a unified lead intake platform that captures leads from websites, portals, webinars, events, partners, and imported lists, ensuring validation, deduplication, consent management, and enrichment.
Build AI-powered lead qualification and scoring capabilities using signals such as product usage, learning activity, website behavior, intent data, and company information.
Create intelligent lead routing systems that assign prospects based on territory, team capacity, availability, and priority, with transparent decision records.
Improve lead hand-offs by tracking each prospect from initial capture to first sales interaction, identifying delays, and ensuring timely follow-up.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline
Join a technology-driven team building the next generation of AI-powered marketing infrastructure. In this role, you will strengthen and evolve the systems that support complex marketing operations, lead management, and data governance.
Responsibilities
Develop a unified lead intake platform that captures leads from websites, portals, webinars, events, partners, and imported lists, ensuring validation, deduplication, consent management, and enrichment.
Build AI-powered lead qualification and scoring capabilities using signals such as product usage, learning activity, website behavior, intent data, and company information.
Create intelligent lead routing systems that assign prospects based on territory, team capacity, availability, and priority, with transparent decision records.
Improve lead hand-offs by tracking each prospect from initial capture to first sales interaction, identifying delays, and ensuring timely follow-up.
Develop a self-service campaign management layer that allows Marketing Operations to configure routing, prioritization, and nurturing rules without creating additional workflows.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline
Join a technology-driven team building the next generation of AI-powered marketing infrastructure. In this role, you will strengthen and evolve the systems that support complex marketing operations, lead management, and data governance.
Responsibilities
Develop a unified lead intake platform that captures leads from websites, portals, webinars, events, partners, and imported lists, ensuring validation, deduplication, consent management, and enrichment.
Build AI-powered lead qualification and scoring capabilities using signals such as product usage, learning activity, website behavior, intent data, and company information.
Create intelligent lead routing systems that assign prospects based on territory, team capacity, availability, and priority, with transparent decision records.
Improve lead hand-offs by tracking each prospect from initial capture to first sales interaction, identifying delays, and ensuring timely follow-up.
Develop a self-service campaign management layer that allows Marketing Operations to configure routing, prioritization, and nurturing rules without creating additional workflows.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline
Join a technology-driven team building the next generation of AI-powered marketing infrastructure. In this role, you will strengthen and evolve the systems that support complex marketing operations, lead management, and data governance.
Responsibilities
Develop a unified lead intake platform that captures leads from websites, portals, webinars, events, partners, and imported lists, ensuring validation, deduplication, consent management, and enrichment.
Build AI-powered lead qualification and scoring capabilities using signals such as product usage, learning activity, website behavior, intent data, and company information.
Create intelligent lead routing systems that assign prospects based on territory, team capacity, availability, and priority, with transparent decision records.
Improve lead hand-offs by tracking each prospect from initial capture to first sales interaction, identifying delays, and ensuring timely follow-up.
Develop a self-service campaign management layer that allows Marketing Operations to configure routing, prioritization, and nurturing rules without creating additional workflows.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline
Join a technology-driven team building the next generation of AI-powered marketing infrastructure. In this role, you will strengthen and evolve the systems that support complex marketing operations, lead management, and data governance.
Responsibilities
Design, build, and operate the next generation of marketing technology while ensuring existing systems remain reliable throughout the transition.
Develop a unified lead intake platform that captures leads from websites, portals, webinars, events, partners, and imported lists, ensuring validation, deduplication, consent management, and enrichment.
Build AI-powered lead qualification and scoring capabilities using signals such as product usage, learning activity, website behavior, intent data, and company information.
Create intelligent lead routing systems that assign prospects based on territory, team capacity, availability, and priority, with transparent decision records.
Improve lead hand-offs by tracking each prospect from initial capture to first sales interaction, identifying delays, and ensuring timely follow-up.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline
Build and operate the AI platform that powers every agent at Polygon Labs, including agent runtime, MCP servers, guardrails, evaluations, observability, and spend tracking.
Responsibilities
Move agentic workflows into production, taking prototypes to robust systems for real users and owners
Build and manage MCP servers, including system design, hosting, security, authentication, and connector inventory
Develop autonomous agents that act and plan across tools through trust stages
Embed guardrails into the platform, providing each agent its own identity, scoped credentials, audit logs, CI checks, approval gates, allowlists, and least-privilege access
Build evaluation frameworks so every agent releases with quality metrics tied to business outcomes
Lead full stack engineering for the Enkrypt Platform, bridging US and India teams, owning production services, and driving reliability and feature delivery.
Compensation
The base salary range for this role is $141,500 - $190,500, along with annual bonus potential, equity participation, and benefits.
Responsibilities
Design and ship full stack features across Next.js/React/TypeScript dashboard and Python/FastAPI backend services
Build secure, versioned APIs and extend Kong API gateway with custom plugins
Develop async workloads on Argo Workflows and NATS JetStream, owning GitOps deployments through ArgoCD, Helm, and Kubernetes
Improve reliability, latency, and observability for production services using OpenTelemetry, Prometheus, and Grafana
Productionize research team capabilities into production-ready code
Own and operate the Kafka estate behind an event-driven integration platform, ensuring delivery guarantees, observability, capacity planning, and infrastructure resilience.
Compensation
Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
Responsibilities
Own the Kafka estate — topic design and naming standards, partitioning and keying strategy, replication, retention and compaction policy, consumer group and offset management, quotas, and broker configuration and upgrades.
Engineer the platform's delivery guarantees in practice: at-least-once and exactly-once semantics, idempotent producers, transactional writes where warranted, dead-letter topics, and self-service replay tooling for recovering from downstream failures.
Build streaming observability: consumer lag, queue depth, throughput and rebalance monitoring; end-to-end correlation-ID tracing across topics; dashboards, service level objectives and alerting.
Plan capacity, cost and retention for a durable log with regulatory audit retention requirements, and tune it as adoption scales across the firm.
Evaluate and integrate vendor-native streaming and change-data-capture mechanisms as the platform's ingress and egress paths mature.
Own and operate the Kafka estate behind an event-driven integration platform.
Compensation
Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
Responsibilities
Own the Kafka estate — topic design and naming standards, partitioning and keying strategy, replication, retention and compaction policy, consumer group and offset management, quotas, and broker configuration and upgrades.
Engineer the platform's delivery guarantees in practice: at-least-once and exactly-once semantics, idempotent producers, transactional writes where warranted, dead-letter topics, and self-service replay tooling for recovering from downstream failures.
Build streaming observability: consumer lag, queue depth, throughput and rebalance monitoring; end-to-end correlation-ID tracing across topics; dashboards, service level objectives and alerting.
Plan capacity, cost and retention for a durable log with regulatory audit retention requirements, and tune it as adoption scales across the firm.
Evaluate and integrate vendor-native streaming and change-data-capture mechanisms as the platform's ingress and egress paths mature.
Own and operate the Kafka estate behind an event-driven integration platform.
Compensation
Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
Responsibilities
Own the Kafka estate — topic design and naming standards, partitioning and keying strategy, replication, retention and compaction policy, consumer group and offset management, quotas, and broker configuration and upgrades.
Engineer the platform's delivery guarantees in practice: at-least-once and exactly-once semantics, idempotent producers, transactional writes, dead-letter topics, and self-service replay tooling for recovering from downstream failures.
Build streaming observability: consumer lag, queue depth, throughput and rebalance monitoring; end-to-end correlation-ID tracing across topics; dashboards, service level objectives and alerting.
Plan capacity, cost and retention for a durable log with regulatory audit retention requirements, and tune it as adoption scales across the firm.
Evaluate and integrate vendor-native streaming and change-data-capture mechanisms as the platform's ingress and egress paths mature.
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