Enterprise AI Solutions Strategist

5 days ago

Davangere, Karnataka, India beBeeGenerative Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Title: Generative AI Architect

We are seeking a visionary technologist with extensive experience in enterprise-scale GenAI solutions, including deep expertise in fine-tuning foundational models.

The ideal candidate will have strong hands-on experience with cloud platforms and a passion for building scalable, innovative GenAI applications using modern frameworks and cloud-native technologies.

Key Responsibilities:

  • Solution Architecture: Lead the design and architecture of GenAI solutions using LLMs and advanced conversational AI frameworks.
  • Model Development: Fine-tune LLMs and SLMs using techniques like PEFT, LoRA, and QLoRA for domain-specific use cases.
  • Open-Source Frameworks: Build GenAI solutions using tools like Hugging Face, LangChain, LangGraph, and AutoGen.
  • Cloud Expertise:
  • Design and deploy scalable AI solutions using GCP services such as Vertex AI, BigQuery, AI Platform, and Cloud Functions.
  • Optimize model performance, cost-efficiency, and reliability within cloud environments.
  • Integration and Deployment:
  • Integrate generative AI models into enterprise systems and applications.
  • Implement robust MLOps practices, including CI/CD pipelines (e.g., GitHub, Jenkins), and containerization using Docker and Kubernetes.
  • Coding and Development:
  • Write clean, maintainable Python code for GenAI applications.
  • Data Preprocessing: Build and maintain data pipelines for training and fine-tuning models.
  • Model Evaluation: Evaluate model performance using relevant metrics and benchmarks; iterate to improve outcomes.
  • Prototyping:
  • Rapidly prototype GenAI applications to demonstrate capabilities.
  • Showcase solutions to stakeholders for feedback and iteration.
  • Drive innovation through fast experimentation and proof-of-concept development.
  • Research & Innovation:
  • Stay current with emerging trends in GenAI and contribute to the evolution of AI architecture and development practices.

Requirements:

  • Bachelor's, Master's, or PhD in Computer Science, AI, Electrical Engineering, or Applied Mathematics.
  • 15–18 years of experience in software architecture and AI/ML systems.
  • Expert-level experience with Google Cloud Platform (GCP), and strong expertise in Microsoft Azure and Amazon Web Services (AWS) for deploying, monitoring, and optimizing AI workloads across cloud environments.
  • Proficiency in Python, with deep knowledge of ML/DL frameworks like PyTorch and TensorFlow.
  • Experience in fine-tuning and deploying LLMs using modern techniques and tools.
  • Familiarity with MLOps platforms and workflows (MLFlow, Kubeflow, Airflow).
  • Excellent communication and leadership skills, with the ability to influence cross-functional teams and drive innovation.

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