Job Title

Job Description:Role: AI ArchitectLocation: PAN India (Remote/Work From Home)Enterprise-Scale AI Solution Design: Designs full-stack conversational AI solutions using Google CCAI, Vertex AI, and custom LLM pipelines. Leads architecture for virtual agents (text/voice), agent assist, and AI-driven analytics Generative AI (Vertex AI, PaLM, GPT-4)Designs and governs GenAI applications: summarization, Q&A, document intelligence. Manages model selection, prompt architecture, grounding strategies, and safety guardrails. Conversational Architecture (Dialogflow CX + Voice). Oversees state machine design, omnichannel integration, and multilingual bot scaling Architects fallback logic, entity modeling, webhook orchestration, and call flow transitionsData Engineering & Pipeline Strategy: Designs ingestion and transformation flows using BigQuery, Dataflow, Pub/Sub, Cloud Storage. Aligns data pipelines to support feature engineering and real-time inferenceMLOps & Continuous Deployment: Implements scalable training/inference workflows using Vertex Pipelines, TensorFlow Extended, or Kubeflow, Versioning, CI/CD, reproducibility, and rollback capabilities built into the ML lifecycleKnowledge Base & Embedding Systems: Integrates unstructured data pipelines using LangChain, LlamaIndex, Pinecone, Vector SearchGoogle Agent Assist & Speech Systems: Configures Agent Assist triggers, STT tuning (noise handling, custom lexicons), and Smart Reply modules. Architects seamless escalation logic and real-time transcription pipelinesVoice AI Design: Leads telephony integration (SIP, PSTN), IVR workflows, and low-latency voice bot optimization. Balances TTS/STT integration with call handling logic and human-agent transfer workflowsTesting & Validation Strategy: Defines testing standards for LLM responses, STT accuracy, webhook logic, and CI automation. Leads model evaluation, prompt regression testing, and safety testing across pipelinesAI Governance & Compliance: Implements data privacy standards (e.g., HIPAA, GDPR), PII handling, and audit logging. Establishes ethical AI use guidelines, fallback safety protocols, and model monitoringExecutive-Level Reporting: Defines KPIs for AI success: containment rate, CSAT lift, time-to-resolution, and NPS. Oversees dashboards (Looker, Tableau) and insight generation for product, ops, and leadershipCross-Functional Collaboration: Leads teams of developers, analysts, QA, and business leads through Agile execution. Conducts architectural reviews, sprint planning, and stakeholder demosTools & Platforms::Languages: Python, SQL, Node.js Cloud: GCP (Vertex AI, BigQuery, Dialogflow CX, Cloud Functions, Cloud Run, IAM) AI Tools: LangChain, Pinecone, LlamaIndex, OpenAI APIs Testing: Postman, Selenium, PyTest, JMeter, CI/CD (Cloud Build/GitHub Actions) Visualization: Looker, Data Studio, Tableau Project Management: Jira, Confluence, Figma (for conversational UX review)