Lead the development and deployment of AI-powered platforms and tools that enhance productivity across core business functions such as Finance, HR, IT, Marketing, Procurement, and Supply Chain.
Identify, evaluate, and implement off-the-shelf AI agents to streamline operations, reduce costs, and accelerate business processes.
Architect and deploy enterprise-grade LLM applications (RAG, Fine-tuning, Agentic workflows) to automate complex processes.
Act as the technical consultant for non-technical leads in Finance (forecasting), Legal (contract analysis), HR (talent matching), and Marketing (content personalization).
Build autonomous AI agents capable of navigating multi-step business tasks with minimal human intervention.
Collaborate with the Data Analytics team to ensure all AI deployments adhere to strict data privacy, security, and "responsible AI" standards.
Manage the lifecycle of AI products from prompt engineering and model selection (GPT-4, Claude, Llama 3, etc.) to integration with internal APIs and databases.

Requirements

5+ years in Data Engineering, Software Engineering, or Data Science, with at least 2+ years of hands-on experience deploying GenAI/LLMs in a production enterprise environment.
Deep proficiency in Python and frameworks such as LangChain, LlamaIndex, or AutoGen.
Experience with cloud AI services (Azure OpenAI, AWS Bedrock, or Google Vertex AI) and vector databases (Pinecone, Weaviate, or Milvus).
Proven ability to translate "business pain" into "technical requirements." You need to speak "Legal" and "Finance" as fluently as you speak "Python."

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonGenAILLMsRAGFine-tuningAgentic workflowsprompt engineeringmodel selectioncloud AI servicesvector databases

Soft Skills

technical consultingcollaborationcommunicationproblem-solvingtranslating business pain into technical requirements