EasyBee AI
Technical Customer Implementation & Success Engineer
EasyBee AI, Boston, Massachusetts, us, 02298
Technical Customer Implementation & Success Engineer
Join to apply for the
Technical Customer Implementation & Success Engineer
role at
EasyBee AI
About the Role As the primary
technical architect
and
trusted advisor
for the customer journey after sale, you will own the end‑to‑end technical implementation of EasyBee AI agents, ensuring seamless integration and optimal performance aligned with customer business objectives. Your responsibilities include:
Develop a structured onboarding plan, setting expectations, milestones, and timelines for implementation.
Lead kickoff calls to gather requirements, align stakeholders, and define the optimal AI agent architecture, including API endpoints, security protocols, and knowledge sessions.
Design, implement, and validate robust ETL pipelines using Python, SQL, or specialized data integration platforms to cleanse, normalize, and ingest customer source data for agent training and operation.
Execute hands‑on configuration and deployment of the AI agent solution, ensuring bidirectional integration with core customer systems (CRM, ERP, FMS, internal data lakes) via managed SDKs, API, or MCP development.
Establish and document initial performance baseline metrics (latency, throughput, error rates) to benchmark optimization efforts.
Work cross‑functionally with engineering, product, and business teams to translate customer needs into implementation steps.
Track progress in Notion and Slack, ensuring accountability and transparency for internal teams and customers.
Customer Success & Adoption
Implement and manage technical dashboards to proactively monitor operational health, resource utilization, and KPIs of deployed AI agents.
Serve as the final technical escalation point for complex integration failures, data sync issues, or agent performance degradation, providing root cause analysis and corrective measures.
Conduct technical workshops and training for customer teams on advanced features, data schema changes, and self‑service tools.
Own post‑implementation engagement, ensuring smooth transitions to everyday use and conducting regular check‑ins, success reviews, and feedback sessions.
Identify upsell or feature expansion opportunities and develop customer playbooks, FAQs, and knowledge bases.
User Acceptance Testing & Quality Assurance
Lead provisioning and configuration of dedicated staging/UAT environment with production parity and data governance compliance.
Develop comprehensive, technically‑focused test cases and scripts for system requirements, load testing, data integrity, and AI agent response accuracy.
Triangulate and manage resolution of technical defects, coordinating with engineering to prioritize and verify fixes.
Systematically document and deliver customer feedback to product teams for continuous improvement.
Continuous Improvement & Process Optimization
Analyze telemetry and logs to identify bottlenecks, tuning infrastructure and code for performance gains.
Produce reusable technical artifacts—deployment scripts, integration blueprints, runbooks, and documentation—to standardize future implementations.
Aggregate field‑level feedback to translate into actionable product requirements.
What Makes You a Great Fit Technical Leadership
Experience with enterprise‑grade integrations (APIs, webhooks, SDKs) across CRMs, ERPs, and FMS platforms.
Proficiency in secure authentication protocols (OAuth2.0, SAML).
Hands‑on data engineering skills: Python, SQL, and preparing data for AI/ML workflows.
Ability to perform deep root cause analysis as the final technical escalation point.
Performance optimization experience, including baselines, telemetry analysis, and infrastructure tuning.
Leadership of UAT setup with structured QA test cases and data integrity checks.
Customer Ownership & Communication
Translate complex technical systems into clear language for executives, business users, and engineers.
Run end‑to‑end onboarding/implementation projects with milestone ownership and stakeholder alignment.
Proactive health monitoring dashboards and usage insights for customer success.
Business acumen to turn customer objectives into scalable technical solutions.
Capture field insights, pain points, and requests to influence roadmap improvements.
Create runbooks, integration playbooks, deployment guides, and reusable scripts.
Co‑author technical case studies and success narratives showcasing measurable outcomes.
Key Performance Indicators
Onboard 100% of new customers within agreed timelines.
Reduce implementation cycle time through process optimizations.
High UAT pass rate with minimal post‑deployment issues.
Increase customer retention and satisfaction (NPS ≥ 8.0).
Identify upsell and expansion opportunities from post‑implementation engagement.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Engineering and Information Technology
Industries Technology, Information and Internet
Pay & Compensation Compensation Details
#J-18808-Ljbffr
Technical Customer Implementation & Success Engineer
role at
EasyBee AI
About the Role As the primary
technical architect
and
trusted advisor
for the customer journey after sale, you will own the end‑to‑end technical implementation of EasyBee AI agents, ensuring seamless integration and optimal performance aligned with customer business objectives. Your responsibilities include:
Develop a structured onboarding plan, setting expectations, milestones, and timelines for implementation.
Lead kickoff calls to gather requirements, align stakeholders, and define the optimal AI agent architecture, including API endpoints, security protocols, and knowledge sessions.
Design, implement, and validate robust ETL pipelines using Python, SQL, or specialized data integration platforms to cleanse, normalize, and ingest customer source data for agent training and operation.
Execute hands‑on configuration and deployment of the AI agent solution, ensuring bidirectional integration with core customer systems (CRM, ERP, FMS, internal data lakes) via managed SDKs, API, or MCP development.
Establish and document initial performance baseline metrics (latency, throughput, error rates) to benchmark optimization efforts.
Work cross‑functionally with engineering, product, and business teams to translate customer needs into implementation steps.
Track progress in Notion and Slack, ensuring accountability and transparency for internal teams and customers.
Customer Success & Adoption
Implement and manage technical dashboards to proactively monitor operational health, resource utilization, and KPIs of deployed AI agents.
Serve as the final technical escalation point for complex integration failures, data sync issues, or agent performance degradation, providing root cause analysis and corrective measures.
Conduct technical workshops and training for customer teams on advanced features, data schema changes, and self‑service tools.
Own post‑implementation engagement, ensuring smooth transitions to everyday use and conducting regular check‑ins, success reviews, and feedback sessions.
Identify upsell or feature expansion opportunities and develop customer playbooks, FAQs, and knowledge bases.
User Acceptance Testing & Quality Assurance
Lead provisioning and configuration of dedicated staging/UAT environment with production parity and data governance compliance.
Develop comprehensive, technically‑focused test cases and scripts for system requirements, load testing, data integrity, and AI agent response accuracy.
Triangulate and manage resolution of technical defects, coordinating with engineering to prioritize and verify fixes.
Systematically document and deliver customer feedback to product teams for continuous improvement.
Continuous Improvement & Process Optimization
Analyze telemetry and logs to identify bottlenecks, tuning infrastructure and code for performance gains.
Produce reusable technical artifacts—deployment scripts, integration blueprints, runbooks, and documentation—to standardize future implementations.
Aggregate field‑level feedback to translate into actionable product requirements.
What Makes You a Great Fit Technical Leadership
Experience with enterprise‑grade integrations (APIs, webhooks, SDKs) across CRMs, ERPs, and FMS platforms.
Proficiency in secure authentication protocols (OAuth2.0, SAML).
Hands‑on data engineering skills: Python, SQL, and preparing data for AI/ML workflows.
Ability to perform deep root cause analysis as the final technical escalation point.
Performance optimization experience, including baselines, telemetry analysis, and infrastructure tuning.
Leadership of UAT setup with structured QA test cases and data integrity checks.
Customer Ownership & Communication
Translate complex technical systems into clear language for executives, business users, and engineers.
Run end‑to‑end onboarding/implementation projects with milestone ownership and stakeholder alignment.
Proactive health monitoring dashboards and usage insights for customer success.
Business acumen to turn customer objectives into scalable technical solutions.
Capture field insights, pain points, and requests to influence roadmap improvements.
Create runbooks, integration playbooks, deployment guides, and reusable scripts.
Co‑author technical case studies and success narratives showcasing measurable outcomes.
Key Performance Indicators
Onboard 100% of new customers within agreed timelines.
Reduce implementation cycle time through process optimizations.
High UAT pass rate with minimal post‑deployment issues.
Increase customer retention and satisfaction (NPS ≥ 8.0).
Identify upsell and expansion opportunities from post‑implementation engagement.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Engineering and Information Technology
Industries Technology, Information and Internet
Pay & Compensation Compensation Details
#J-18808-Ljbffr