Title: Unit Head (Artificial Intelligence- Digital Banking)
Company Name: Mutual Trust Bank PLC
Vacancy: --
Age: Na
Job Location: Dhaka
Salary: --
Experience:
Having a portfolio of past and ongoing AI initiatives having significant, proven impacts.
Hands On experience in LLM and NLP development.
Deep understanding of: Tokenization, Embeddings, Transformers, Sequence modeling, Language modeling, LLM fine-tuning (SFT, LoRA, PEFT), Prompt engineering, Evaluation of downstream models, Traditional NLP (regex, CRFs, SVMs, feature-based models), LangChain, AutoGen, CrewAI, LlamaIndex, LLM inference optimizations, Embedding models & VectorDBs, Ranking algorithms, Time-series models.
End-to-end pipeline experience (research → deployment → monitoring).
Skilled in: Tool calling, Multi-agent orchestration, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Reasoning and planning frameworks, Building tools for APIs, DBs, and web interaction.
Design, develop, and maintain LLM-based AI components, improving efficiency for internal teams and user-facing applications.
Build systems spanning data retrieval, RAG, vector search, chat interfaces, and agentic workflows.
Experiment with and evaluate new LLM architectures, frameworks, and AI/ML toolchains.
Enhance data infrastructure to support high-volume LLM usage, embeddings, and scalable storage.
Collaborate with cross-functional teams (analysts, SWE, operations, product) to define use cases and deliver AI-powered solutions.
Contribute to the company`s technical vision for generative AI foundations.
Conduct quantitative evaluations, benchmarking, and performance optimization of NLP/LLM models.
Integrate NLP and AI components into large-scale production systems, ensuring reliability and low latency.
Develop and maintain text data generation, preprocessing, and training/evaluation pipelines.
Follow best practices in software engineering, testing (TDD), CI/CD, and version control.
Stay updated with the latest LLM advancements (RAG, MCP, Tool Use, ReAct, agent systems).
Build end-to-end NLP/LLM applications from research → deployment → monitoring.