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 agile 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.

📌 Senior Engineer - AI Engineering and Data Science (Gurugram)
🏢 OYO
📍 Gurugram