Principal AI Solutions Architect

Experience: 12.00 + years Salary: Confidential (based on experience) Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Hybrid (Chennai) Placement Type: Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Five9) What do you need for this opportunity Must have skills required: AI Stack, Technical Architecture, cloud platforms, integration design, Security, Data flows, Ml engineering, Contact Center, responsible-AI, architecture patterns, Cloud certifications, enterprise architecture Five9 is Looking for: Principal AI Solutions Architect ABOUT THE ROLE Five9 is a leading provider of cloud contact center software, bringing the power of Five9 AI and automation to organizations worldwide. The Enterprise-AI Team drives Five9's internal adoption of AI turning emerging capability into real business outcomes across the company. The Principal AI Solutions Architect is the most senior technical voice on the team and the design authority for Five9's internal AI work the person who turns an approved solution concept into a buildable technical architecture. You partner with the business-facing solutions lead, who owns what a solution must achieve and why; you own how it is built the reference architecture, data and integration design, model / agent / platform selection, security and governance fit, and the technical standards the engineering team builds to. The role demands someone who stays current at all times on the fast-moving AI platform, model, agent, and tooling landscape and on emerging architecture patterns, so every design reflects the best available approach and is sound, secure, and feasible before the build begins. HOW YOU CONTRIBUTE Technical solution design Translate an approved solution concept into an end-to-end technical architecture components, data flows, integration and API surface, model / agent selection, and non-functional requirements captured as a clear, buildable design.Reference architecture & standards Define and maintain the reusable patterns, guardrails, and technical standards the engineering team builds to; keep them current as capabilities and tooling evolve.Platform & build-vs-buy strategy Evaluate models, vendors, frameworks, and cloud-platform options; recommend fit, cost, and trade-offs with a clear rationale.Data & integration design Design how each solution accesses, moves, and secures company and business data; define the integrations and interfaces the build requires.Security, governance & responsible-AI fit Design to information-security, data-classification, and responsible-AI requirements from the start; carry designs through architecture and security review.Design handoff & build support Package the technical design to a buildable standard and support the engineering team through implementation as their technical counterpart.Continuous currency Maintain always-current command of the AI platform, model, agent, and tooling landscape and emerging architecture patterns, so every design reflects the best available approach.Technical advisory Advise business partners, engineers, and leadership on feasibility, risk, effort, and sequencing; pressure-test solution designs for technical soundness before they advance.Cross-functional partnership Partner with enterprise architecture, information security, and platform / DevOps teams so designs move cleanly from concept into governed delivery.SKILLS, COMPETENCIES & QUALIFICATIONS REQUIRED Bachelor's degree (or equivalent experience) in Computer Science, Engineering, Information Systems, or a related field.12+ years in solution / software / enterprise architecture, ML / AI engineering, or technical solutions / pre-sales engineering including hands-on design of production systems and setting technical direction others build to.Demonstrated ability to design end-to-end technical architectures for AI / ML or data-intensive systems (components, data flows, integrations, non-functionals, and security).Strong command of the modern AI stack LLMs, agent frameworks, retrieval / RAG, orchestration, tool integration, AI-augmented development with a demonstrated habit of staying continuously current.Hands-on experience with cloud platforms (Google Cloud preferred) and modern delivery tooling (Git-based version control, CI / CD, infrastructure-as-code).Ability to produce clear, buildable architecture artifacts (reference diagrams, data / integration designs, architecture decision records) and communicate them to both engineers and executives.Working knowledge of security, data-classification, and responsible-AI requirements in an enterprise setting.SKILLS, COMPETENCIES & QUALIFICATIONS PREFERRED Experience in or with contact center / CX technology (Five9 or comparable), or applying AI to CX.Familiarity with responsible-AI .