Pre Sales Solution Architect

Title: Technical Solutions Architect

Practice: AI & Contact Center Transformation
Focus: Technical Architecture, Platform Engineering, & Integration Design (Presales & Early Delivery)

ROLE SUMMARY

The Technical Solutions Architect is the technical authority responsible for designing, validating, and architecting AI-powered contact center solutions that are scalable, secure, and operationally sound. You translate business requirements into detailed technical blueprints, working closely with presales teams, Solution Consultants, and client IT/engineering stakeholders to ensure solutions are feasible, performant, and aligned with enterprise architecture standards.

Your primary focus is on the technical design and integration strategy —ensuring that AI agents, CCaaS platforms, CRM systems, and enterprise data layers work together seamlessly. You will lead technical discovery, design solution architectures, validate integrations, and provide the engineering guardrails that enable successful delivery by POD teams.

You ensure that what we sell can actually be built—and built well.

KEY RESPONSIBILITIES

1. Technical Discovery & Infrastructure Assessment

• Lead technical discovery sessions with client IT, telephony, and infrastructure teams to assess current environment and readiness.
• Evaluate existing CCaaS platforms (Genesys Cloud/Engage, Five9, NICE CXone, Amazon Connect, Twilio, etc.) for AI agent integration capabilities.
• Assess CRM such as ServiceNow/MS Dynamics/Salesforce, knowledge base, and backend system APIs for data accessibility, and integration feasibility.
• Analyze telephony infrastructure (SIP trunking, IVR legacy systems, call routing) and identify migration or integration requirements.
• Identify technical risks, constraints, and dependencies (network latency, API rate limits, data compliance, PII/PCI requirements).

2. AI Agent & CCaaS Platform Architecture Design

• Design end-to-end technical architectures for AI agent deployments, including conversational AI platforms, LLM orchestration, knowledge retrieval (RAG), and real-time integrations.
• Define integration patterns between AI agent platforms and CCaaS environments.
• Architect omnichannel solutions spanning voice, chat, SMS, and digital channels with consistent agent behavior and context management.
• Design call flow logic, escalation routing, fallback strategies, and human-in-the-loop handoff mechanisms.
• Define data flow diagrams, API contracts, authentication/authorization schemes (OAuth, API keys, SSO), and middleware requirements.

3. Integration & Data Architecture

• Design integration architecture for connecting AI agents to backend systems: CRMs, ERPs, billing systems, knowledge bases, and ticketing platforms.
• Define data schemas, payload structures, and real-time vs. batch integration strategies.
• Architect secure data handling for PII, PCI-DSS, HIPAA, or GDPR-compliant environments, including data masking, encryption, and audit logging.

4. Platform Selection & Technical Validation

• Conduct technical proof-of-concepts (POCs) and feasibility studies to validate platform capabilities, integration complexity, and performance benchmarks.
• Assess CCaaS native AI capabilities vs. third-party AI agent platforms to determine optimal architecture.
• Define build vs. buy strategies for conversational components, analytics, and quality management tools.

5. Presales Technical Enablement & RFP Response

• Partner with Solution Consultants during presales to provide technical depth, validate feasibility, and design proposed architectures.
• Lead technical portions of client presentations, solution demos, and architecture review sessions.
• Author technical sections of RFPs, RFIs, and SOWs, including architecture diagrams, integration specifications, and infrastructure requirements.
• Articulate technical differentiators, platform advantages, and engineering best practices to client technical stakeholders.
• Defend solution designs against client technical objections and provide alternative approaches when needed.

6. SOW Scoping & Engineering Handoff

• Define detailed technical scope for Statements of Work (SOWs), including integration points, data requirements, infrastructure dependencies, and deliverables.
• Specify technical assumptions, constraints, and exclusions to protect delivery feasibility and margins.
• Create engineering handoff documentation: architecture diagrams, integration specs, API documentation, and technical requirements.
• Conduct transition sessions with Delivery PODs to ensure technical intent, design rationale, and risk mitigation strategies are clearly understood.
• Participate in design reviews and critical milestones (e.g., technical design approval, integration validation, UAT) to ensure delivery aligns with architecture.

REQUIRED QUALIFICATIONS

• 5+ years of experience in  Solutions Architecture, Technical Presales, or Platform Engineering , with a focus on contact center or enterprise communication platforms.
• Deep CCaaS Expertise: Hands-on experience with at least two major CCaaS platforms (Genesys Cloud/Engage, Five9, NICE CXone, Amazon Connect, Twilio Flex, Cisco Webex Contact Center).
• AI Agent & Conversational AI Knowledge: Familiarity with AI agent platforms, LLM orchestration, NLU/NLP, intent recognition, dialogue management, and knowledge retrieval (RAG).
• Integration Architecture: Proven experience designing RESTful APIs, webhooks, middleware , and real-time data integration patterns.
• Technical Communication: Ability to translate complex technical concepts for non-technical stakeholders and defend architectural decisions with technical teams.
• Cloud & Infrastructure: Experience with AWS, Azure, or GCP; understanding of compute, networking, security, and serverless architectures.

PREFERRED QUALIFICATIONS

• Experience with  AI agent platforms
• Hands-on experience with  telephony protocols
• Experience in  regulated industries (financial services, healthcare, utilities) with PCI-DSS, HIPAA, or GDPR compliance requirements.
• Certifications in cloud platforms (AWS Solutions Architect, Azure Solutions Architect) or CCaaS platforms (Genesys, Five9, NICE).

KEY SUCCESS METRICS

• Quality and feasibility of technical architectures and integration designs.
• Client technical stakeholder confidence in proposed solution and delivery approach.
• Accuracy of technical scoping in SOWs (minimal scope creep or technical surprises during delivery).
• Successful engineering handoffs with clear, actionable technical documentation.
• Delivery POD velocity and technical alignment with original architecture vision.
• Contribution to won deals through technical credibility and solution differentiation.