About Us :
CLOUDSUFI, a Google Cloud Premier Partner, a Data Science and Product Engineering organization building Products and Solutions for Technology and Enterprise industries. We firmly believe in the power of data to transform businesses and make better decisions. We combine unmatched experience in business processes with cutting edge infrastructure and cloud services. We partner with our customers to monetize their data and make enterprise data dance.
Our Values :
We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.
Equal Opportunity Statement :
CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace.
Role : Lead AI/Senior Engineer-AI
Location : Noida, Delhi/NCR
Experience : 5- 12 years
Education : BTech / BE / MCA / MSc Computer Science
Must Haves :
Conversational AI & NLU :
- Advanced proficiency with Dialogflow CX
- Intent classification, entity extraction, conversation flow design
- Experience building structured dialogue flows with routing logic CCAI platform familiarity
Agentic AI & Multi-Step Reasoning :
- Production experience with Google ADK (or LangChain/LangGraph equivalent)
- Multi-step reasoning and tool orchestration capability
- Tool-use patterns and function calling implementation
RAG Systems & Knowledge Management :
- Hands-on Vertex AI RAG Engine experience (or equivalent)
- Semantic search, chunking strategies, retrieval optimization
- Document processing pipelines (PDF parsing, chunking)
LLM/GenAI & Prompt Engineering :
- Production experience with Gemini models
- Advanced prompt engineering for customer support
- Langfuse experience for prompt management
Google Cloud Platform & Vertex AI :
- Advanced Vertex AI proficiency (Generative AI APIs, Agent Engine)
- Cloud Functions and Cloud Run deployment experience
- BigQuery for conversation analytics
API Integration :
- Genesys Cloud CX integration experience
- REST API design and webhook implementation
- Enterprise authentication patterns (OAuth 2.0)
Good To Have :
Conversational AI & NLU :
- Multi-language support implementation (Spanish/English)
- Telephony integration (speech recognition, TTS, DTMF)
- Barge-in handling and voice optimization
Agentic AI :
- Agent state management and session persistence
- Advanced fallback strategies and error recovery
- Dynamic tool selection and evaluation
RAG Systems :
- Re-ranking and advanced retrieval quality metrics
- Query expansion and context-aware retrieval
- Corpus organization strategies
LLM/GenAI :
- Prompt versioning, A/B testing, iterative refinement
- Prompt injection mitigation strategies
- In-context learning, few-shot, chain-of-thought techniques
LLMOps & Observability :
- Vertex AI Evaluation Service experience
- Groundedness, relevance, coherence, safety metrics
- Trace-level debugging with Cloud Trace
- Centralized logging strategies
Google Cloud :
- Application Integration connectors
- VPC Service Controls and enterprise security
- Cloud Pub/Sub for event-driven systems
Enterprise Integration :
- Third-party AI agent orchestration (SAP Joule, ServiceNow AI, Agentforce)
- Salesforce, SAP, ServiceNow integration patterns
- Context passage strategies for escalations
Architecture & System Design :
- Configuration-driven systems (Meta-Agent patterns)
- Microservices and containerization
- Scalable, multi-tenant system design
- Disaster recovery and failover strategies
Product Quality & KPIs :
- Customer support metrics expertise (CSAT, SSR, escalation rate)
- A/B testing and experimentation frameworks
- User feedback loop implementation
Deliverables :
- Architecture Design : End-to-end platform architecture, data flow diagrams, Dialogflow CX vs. ADK routing decisions
- Conversational Flows : 15+ dialogue flows covering billing, networking, appointments, troubleshooting, and escalations
- ADK Agent Implementation : Complex reasoning agents for technical support, account analysis, and context preparation
- RAG Pipeline : Document processing, chunking configuration, corpus organization (product docs, support articles, policies, promotions)
- Prompt Management : System prompts, Langfuse setup, playbook governance, version control
- Quality Framework : Evaluation pipeline, metrics dashboards, automated assessment, continuous improvement recommendations
- Integration Layer : Genesys handoff, webhook integrations, Application Integration setup, session management
- Testing & Validation : Conversation flow tests, performance testing (latency, throughput, 1000 concurrent users), security validation
- Response time <2 seconds (p95), 99.9% uptime, 1000 concurrent conversations
- Data encryption (TLS 1.2+, AES-256 at rest), PII redaction, 1-year data retention
- Graceful degradation and fallback mechanisms
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