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Urgent! GenAI Lead Engineer (Investment Data Platforms) Job Opening In Shivamogga – Now Hiring Vichara Technologies

GenAI Lead Engineer (Investment Data Platforms)



Job description

We are seeking a highly skilled GenAI Lead Engineer to design and implement advanced frameworks for alternate data analysis in the investment management domain.

The candidate will leverage LLM APIs (GPT, LLaMA, etc.) , build scalable orchestration pipelines, and architect cloud/private deployments to power next-generation AI-driven investment insights.

This role will also involve leading a cross-functional team of Machine Learning Engineers and UI Developers to deliver robust, production-ready solutions.

Responsibilities

  • GenAI Framework Development - Develop custom frameworks using GPT APIs or LLaMA for alternate data analysis and insights generation.

    Optimize LLM usage for investment-specific workflows, including data enrichment, summarization, and predictive analysis.

  • Automation & Orchestration - Design and implement document ingestion workflows using tools such as n8n (or similar orchestration frameworks).

    Build modular pipelines for structured and unstructured data.

  • Infrastructure & Deployment - Architect deployment strategies on cloud (AWS, GCP, Azure) or private compute environments (CoreWeave, on-premises GPU clusters) .

    Ensure high availability, scalability, and security in deployed AI systems.


Required Candidate Profile

  • Strong proficiency in Python with experience in frameworks such as TensorFlow or PyTorch .

  • 2+ years of experience in Generative AI and Large Language Models (LLMs) .

  • Experience with VectorDBs (e.g., Pinecone, Weaviate, Milvus, FAISS) and document ingestion pipelines.

  • Familiarity with data orchestration tools (e.g., n8n, Airflow, LangChain Agents).

  • Understanding of cloud deployments and GPU infrastructure (CoreWeave or equivalent).

  • Proven leadership skills with experience managing cross-functional engineering teams .

  • Strong problem-solving skills and ability to work in fast-paced, data-driven environments.

  • Experience with financial or investment data platforms .

  • Knowledge of RAG (Retrieval-Augmented Generation) systems.

  • Familiarity with frontend integration for AI-powered applications.

  • Exposure to MLOps practices for continuous training and deployment.


Required Skill Profession

Computer Occupations



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