Senior Engineer - AI Engineering and Data Science

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.