Advanced AI Systems Specialist

4 days ago

Lucknow, Uttar Pradesh, India beBeeDeveloper Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Job Title: Intelligent System Developer

We are seeking a highly skilled Intelligent System Developer to play a critical role in the development, automation, and deployment of advanced AI and machine learning pipelines across cloud environments.

This hands-on role emphasizes building robust workflows, integrating observability tools, and enabling efficient, scalable model delivery. The position supports complex AI systems deployed in banking environments, where resilience and reliability are paramount.

  • Key Experience:
  • 3-5 years Strong programming skills in Python, with experience in pandas, SQL, and ML frameworks (e.g., scikit-learn).
  • Proficiency in using Python in the ML domain to build, train, and maintain models.
  • Familiarity with AWS services such as Lambda, Glue, CloudWatch, and Bedrock.
  • Experience with containerized workflows (Docker) and model lifecycle management.
  • Foundational knowledge of observability practices and model deployment fundamentals.
  • Interest or experience in supporting AI systems used by developers or analysts.
  • Strong communication and documentation skills with a collaborative team mindset.
  • Ability to assume ownership of assignments and consistently meet deadlines.

Responsibilities:

  • Deploy and maintain AI and GenAI models using AWS services, including SageMaker, Fargate, and Bedrock.
  • Apply prompt engineering techniques to optimize GenAI model performance and reliability.
  • Experience with Retrieval-Augmented Generation (RAG) applications is a plus.
  • Assist in building and maintaining internal model-serving platforms to support development teams.
  • Implement containerized services using Docker and deploy them to AWS infrastructure.
  • Write Infrastructure-as-Code (IaC) using Terraform to automate cloud resource provisioning (nice to have).
  • Participate in unit and end-to-end testing of AI pipelines, services, and monitoring workflows.
  • Support model monitoring and health tracking using AWS CloudWatch and internal observability tools.
  • Document internal systems and operational processes to ensure maintainability and reproducibility.

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