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* Build AI-driven internal applications using Databricks (Python, MLflow, Unity Catalog, Model Serving).
* Design, fine-tune, and deploy custom chatbots trained on private enterprise data (vector search, retrieval augmentation, LLM orchestration).
* Integrate Databricks models with internal web apps, APIs, and tools already used inside the bank.
* Build pipelines that handle ingestion, cleaning, indexing, and securing sensitive datasets.
* Own the full lifecycle: discovery → architecture → delivery → monitoring.
* Work closely with internal stakeholders (BI, Data Engineering, Ops, Risk, Compliance) to bring working AI solutions into production.
* Operate with a "solve it first, explain it later" mindset - rapid prototyping, fast iteration, and clean handovers.
* Strong Python engineering background; comfortable building production-quality code.
* Hands-on experience with Databricks (workflows, Delta Live Tables, Unity Catalog, MLflow, Model Serving).
* Experience building AI chatbots, RAG pipelines, vector search, embedding stores, and private LLM deployments.
* Understanding of architectural patterns for secure deployment in financial institutions.
* Ability to independently take vague business problems and convert them into concrete AI products.
* Comfortable demoing your work to senior stakeholders.
Databricks with AI
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