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)