Lead AI Engineer at Sutherland

Role: Lead AI Engineer – Case Management & Analytics We are seeking a highly experienced Lead AI Engineer to design, build, and scale AI-driven platforms and solutions focused on case management, customer service optimization, and analytics-driven insights. This role combines hands-on AI engineering, driving intelligent automation across case workflows, contact center operations, and enterprise applications. You will collaborate with business stakeholders, data scientists, and engineering teams to deliver scalable, cloud-native AI solutions powered by Machine Learning (ML) and Generative AI. Key Responsibilities • Develop AI models for case classification, routing, prioritization, and SLA prediction. • Build automation for email-to-case, summaries, call notes, and CRM/workflow updates. • Deliver AI-driven insights including sentiment analysis, anomaly detection, and forecasting. • Design and implement LLM/RAG-based knowledge retrieval and AI copilots. • Build and integrate AI services with CRMs, contact center platforms, and enterprise systems. • Architect data pipelines, embeddings, and vector-based search solutions. • Deploy scalable AI solutions using cloud AI services (Azure AI, AWS AI, Google Vertex AI / Gemini) • Establish MLOps, CI/CD, and containerized deployment practices. • Lead AI architecture, governance, and cross-functional collaboration.  Skills & Qualifications • Bachelor’s degree in Computer Science, Engineering, or related field. • 10–15+ years of experience in application development and AI/ML engineering. • Proven experience building and scaling AI-driven platforms and solutions. • Strong hands-on experience in Python, NLP, Machine Learning, and Generative AI/LLMs. • Experience with vector databases (FAISS, Milvus, Weaviate) and RAG pipelines. • Hands-on experience designing and implementing Agentic AI systems, including autonomous agents, multi-agent orchestration, task planning, tool integration, and reasoning workflows. • Experience building AI agents using frameworks such as LangChain, LangGraph, AutoGen, or similar ecosystems. • Familiarity with MLOps, CI/CD, Docker, and KubernetesPreferred Skills • Knowledge of contact center platforms such as Cisco, Genesys, NICE, or Avaya. • Experience building AI copilots, chatbots, and agent-assist solutions. • Familiarity with knowledge systems, enterprise search, and recommendation engines. • Experience working with LLM platforms such as OpenAI, Google Gemini, or Claude. • Cloud and AI certifications (Azure, AWS, or Google Cloud)