Job Description
Role & responsibilities :
1. Enterprise AI & Agentic Platform Architecture
Generative AI & Agentic Workflows: Lead the architecture and production scaling of enterprise Generative AI and autonomous agent frameworks (ReAct, LangChain, ADK, multi-agent orchestration) across customer support, recruitment, and procurement operations.
Omnichannel Automation: Oversee production-grade LLM applications across Web Chat, WhatsApp, Email, and Off-Hours Voice Assistants, driving high coverage rates and autonomous resolution thresholds.
2. Machine Learning, Risk Intelligence & Revenue Optimization
Revenue Protection & Predictive ML: Retrain and deploy advanced ML algorithms (CatBoost, XGBoost, Random Forest) for risk modelling, fraud detection, location-intelligence frameworks, and dynamic pricing engines.
Data Quality & Automated Pipelines: Build and maintain automated data-cleaning and ETL pipelines to optimize feature values, eliminate data duplication, and ensure high operational uptime.
3. AI Cost Optimization & Infrastructure Governance
Model Inference & Infrastructure Efficiency: Continuously optimize LLM inference workflows, ASR pipelines, and vector database architectures (ChromaDB, Azure ML) to minimize cloud run-rates and processing latency.
Turnaround Time (TAT) Reduction: Re-architect core data-processing loops to maintain sub-3-hour end-to-end processing times across large-scale business operations.
Candidate Qualifications & Skill Set
Must-Have Technical Expertise:
Generative AI & LLMs: Extensive hands-on experience building RAG pipelines, fine-tuning LLMs, vector database integration, and agentic frameworks (ReAct, LangChain, AutoGen, ADK).
Core Machine Learning & Computer Vision: Proficiency in predictive ML (XGBoost, CatBoost, Scikit-Learn) and vision pipelines (DINOv2, Feature Matching, Face Recognition).
Programming & Backend: High proficiency in Python, FastAPI/Flask, SQL, and RESTful microservices architecture.
Cloud & DevOps: Hands-on experience with Azure ML / AWS, Docker, Kubernetes, CI/CD (GitHub Actions), and vector storage solutions (ChromaDB, Pinecone).
ERP & Speech Integrations: Familiarity with Oracle ERP integrations, ASR frameworks (Azure ACS, Whisper), and speech diarization is a plus.
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