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 Kubernetes
Preferred 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)
All your information will be kept confidential according to EEO guidelines.
