Job Description – AI/LLM Expert (RAG Anomaly Detection Platform)
Position : Senior AI/LLM Architect – RAG, Knowledge Intelligence Anomaly Detection
Key Responsibilities
- Design and implement enterprise Agentic Applications for knowledge processing.
- Develop knowledge ingestion pipelines for structured and unstructured government documents.
- Build semantic search and retrieval systems using Vector Databases and Search Engines.
- Develop anomaly detection models to identify contradictions, policy deviations, and historical inconsistencies.
- Develop Intent Management Systems to understand Documents.
- Fine-tune and optimize LLMs for government and policy-domain use cases.
- Develop explainable AI capabilities, confidence scoring, and audit trails.
- Build APIs and microservices for AI model integration.
Mandatory Technical Skills
- AI / Machine Learning
- Understanding and Integration with Open source Large Language Models (LLMs) like Llama, Mistral, Gemma
- Retrieval-Augmented Generation (RAG)
- Semantic Similarity Text Classification
- Semantic anomaly detection
- Vector Databases (Milvus, Qdrant, Weaviate)
- Search Technologies like Elasticsearch / OpenSearch Hybrid Search (Keyword + Semantic Search)
- Python/PyTorch / TensorFlow
- LangChain / LlamaIndex
Experience Requirements
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
- 6–12 years of software engineering and AI/ML experience.
- Minimum 5 years of hands-on experience in LLM, RAG, NLP, or Generative AI solutions.
- Experience designing enterprise-scale AI platforms handling large document repositories.
- Experience with government, public sector, legal, regulatory, telecom, banking, or compliance-related domains preferred.
Experience with on-premise deployments and security-sensitive environments is highly desirable
