Contact Center Engineer

We are a global leader in unified communications and customer experience solutions. Our platform powers video, voice, chat, and contact center capabilities for organizations of all sizes, helping them connect teams, engage customers, and deliver modern, AI-driven experiences across channels.

Our customer experience and virtual agent products enable organizations to automate and enhance customer interactions through intelligent chat and voice bots integrated into existing contact center and business systems.

Role Summary

We are hiring three Mid-Level Deployment Engineers to focus on hands-on implementation work for smaller mid-market customers. These roles are distinct from senior, enterprise-focused positions and are designed for engineers who execute strongly and are progressing into AI solution delivery, but are not yet at a senior/principal level.

You will configure, deploy, and manage workflows and AI bot configurations for real-world client use cases, such as automating customer service calls and digital support interactions. Ideal candidates have a solid engineering background and hands-on experience with conversational AI / CX tooling (for example, platforms like Cognigy, Cyara, Glean or similar), showing a clear progression from implementation engineering into AI-powered solutions. Prior experience in implementation architecture (high-level design of implementations and integrations) is also a strong fit for this role, provided candidates are comfortable remaining hands-on.

Key Responsibilities

• Implementation & Configuration
• Implement and configure AI chat and voice bots for mid-market customers based on defined requirements and solution designs.
• Set up workflows, routing logic, and interaction flows to support use cases such as:
• Automating customer service and support calls
• Handling common inquiries via chat or messaging
• Integrating with existing systems (CRM, ticketing, knowledge bases, contact center platforms)
• Configure channels, platform settings, and integrations according to best practices and implementation standards.
• Workflow & Bot Management
• Build and maintain bot dialogs, intents, flows, and automation rules using low-code/no-code or configuration-based tools.
• Tune and optimize workflows and configurations based on testing, analytics, and customer feedback.
• Implement business rules, escalation paths, and seamless handoff logic to live agents.
• Technical Delivery
• Translate solution designs from senior engineers, solution architects, or implementation architects into working configurations.
• Execute deployment tasks such as:
• Environment/tenant setup and initial configuration
• Connecting data sources, APIs, and supporting tools (where required)
• Configuration-focused troubleshooting and issue resolution
• Participate in functional and user acceptance testing, and resolve issues related to workflows, routing, and bot behavior.
• Customer & Cross-Functional Collaboration
• Work directly with customer stakeholders (often in collaboration with project managers or senior engineers) to validate behavior, gather configuration details, and support deployment and go-live.
• Partner with Professional Services project managers, sales engineers, and support teams to ensure smooth deployments and clean handoffs to ongoing operations.
• Document implementation details, configuration decisions, and procedures for future maintenance and enhancements.

Required Qualifications

• Engineering / Architecture Background
• Previous experience in an engineering or implementation-focused role (e.g., deployment engineer, implementation engineer, systems engineer, or software engineer involved in solution delivery).
• Prior experience in implementation architecture (e.g., designing how systems, integrations, and workflows fit together for customer deployments) is a strong plus, as long as candidates are comfortable in a hands-on configuration role.
• Strong technical problem-solving skills and comfort working with complex, configuration-driven SaaS platforms.
• Implementation Experience
• Hands-on experience implementing or configuring:
• Conversational AI, virtual agents, or chatbots, and/or
• Contact center, IVR, or telephony solutions, and/or
• Other enterprise CX platforms where workflows and integrations are key.
• Ability to convert business/functional requirements into concrete configuration tasks and detailed implementation steps.
• AI / CX Tooling Exposure
• Experience with one or more tools or platforms in the conversational AI / CX ecosystem (for example, platforms like Cognigy, Cyara, Glean, or comparable technologies).
• Familiarity with concepts like intents, flows, routing, NLU/NLP, and automation in customer service contexts.
• Demonstrated interest in further developing skills in AI-powered customer experience solutions.
• Technical Skills
• Comfort using web-based admin consoles and configuration interfaces.
• Familiarity with:
• Basic API and webhook concepts
• Data and systems integration principles (able to follow implementation guides and collaborate with more technical teams)
• Ability to read and apply technical documentation in real-world deployments.
• Soft Skills
• Strong organizational skills, with the ability to manage multiple mid-market implementations in parallel.
• Clear, concise written and verbal communication, especially when documenting configuration decisions and explaining system behavior to non-technical stakeholders.
• Collaborative, low-ego working style; open to guidance from senior team members and effective in cross-functional teams.

Ideal Background & Profile

• Approximately 2–5 years of experience in implementation or deployment engineering, ideally in enterprise SaaS, contact center, or CX environments.
• A career path that shows progression from general implementation engineering into AI and automation-focused work, potentially including a stint in implementation architecture, without being overly senior.
• Experience working with customers in the mid-market segment, balancing standardization with tailored configuration.
• Motivated to grow into more advanced AI solution delivery while maintaining a strong hands-on, execution-focused role.