Job Description

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We re looking for a Databricks engineer who knows how to ship not theorize You will design build and deploy AI applications inside the bank including custom chatbots trained on private datasets internal automation tools and Databricks powered LLM services If you re the type who takes a problem disappears for a week and comes back with a working prototype you ll fit in well This is not a passive ticket taker role We want someone who operates like a field engineer self directed resourceful and comfortable building end to end solutions in a regulated environment

Key Responsibilities:

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What You ll Do 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

Technical Requirements:

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What You Should Bring 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

Additional Responsibilities:

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Experience with Databricks Mosaic AI vector search model serving agents etc Experience building internal developer tools self service portals or automation bots Strong Git discipline and comfort working with CI CD Exposure to MLOps and governance processes in regulated industries Portfolio Requirements We want to see evidence that you can build Please include at least one of the following in your application GitHub repository showing an AI or LLM based project chatbot agent RAG pipeline ML pipeline service backend etc Demo videos or screenshots of AI tools you ve built Links to deployed models APIs or internal project writeups sanitized for confidentiality If there s no portfolio we ll ask for a technical challenge What Success Looks Like Within 90 days you should be able to Deliver a working prototype of at least one internal AI application Deploy a Databricks served LLM or endpoint consumed by internal teams Build a chatbot or assistant trained on bank specific data sources Raise and solve your own problems without waiting for permission

Preferred Skills:

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Technology->Data Engineering->Databricks,Technology->Artificial Intelligence->Artificial Intelligence - ALL