AI Automation Lead

Cephas Consultancy Services Private Limited

India, Maharashtra, Pune

On-site · Full-time

About the Role

We are seeking a proactive AI engineer with a strong infrastructure background to join our team in Pune. You will design, scale, and optimize high-performance AI platforms, partnering closely with Infrastructure Operations to turn operational challenges into automated, business-aligned AI solutions.

Key Responsibilities

AI and Infrastructure

  • Design, build, and maintain scalable infrastructure, pipelines, and environments for training and deploying AI/ML models.
  • Collaborate with Infrastructure Operations to identify operational bottlenecks and address them with intelligent automation and AI-driven workflows.
  • Optimize GPU and CPU workloads, storage, and compute clusters to balance performance and cost efficiency.

Business and Value-Driven Engineering

  • Translate business goals and operational metrics into concrete AI infrastructure initiatives.
  • Measure and report the return on investment of infrastructure improvements, such as uptime, latency reduction, cloud spend optimization, and developer productivity.
  • Promote a product mindset within the operations unit, focusing on long-term value, system resilience, and scalability.

MLOps and Platform Reliability

  • Establish robust MLOps/LLMOps practices, including CI/CD for ML, automated monitoring, drift detection, and model governance.
  • Implement continuous observability and telemetry for model performance and underlying infrastructure.

What We’re Looking For

Core Qualifications

  • Experience: 12+ years in software or infrastructure engineering, including at least 2 years dedicated to AI/ML infrastructure or MLOps.
  • Infrastructure: Proven experience with cloud architecture (AWS, Azure, or GCP), Kubernetes, Docker, and Infrastructure as Code tools such as Terraform or Ansible.
  • AI/ML Tooling: Experience deploying frameworks such as PyTorch and TensorFlow, and working with vector databases and MLOps tools such as Kubeflow, MLflow, Ray, or Triton Inference Server.
  • Programming: Proficiency in Python, Go, or C++, along with strong shell scripting and Linux skills.

Mindset and Soft Skills

  • Business Acumen: Ability to connect technical architecture decisions to business outcomes, SLAs, and cost management.
  • Problem Solving: Proactive approach to identifying systemic operational challenges and designing durable AI and automation solutions.
  • Collaboration: Strong communication skills and experience partnering with cross-functional teams, including DevOps, Data Science, and business stakeholders.

Mandatory Skills

  • AI/LLM integration for IT operations.
  • Deep hands-on experience with AWS or Azure, including:
    • Cloud architecture design and implementation.
    • Networking, IAM, and security best practices.
    • Infrastructure as Code, including Terraform.
    • Automation scripting with Python or Go.
    • Observability and monitoring solutions.
    • ITSM integration.
    • Practical experience with AI/LLM APIs or Retrieval-Augmented Generation (RAG).

Preferred Qualifications

  • Hands-on experience with LLM infrastructure, fine-tuning setups, or RAG pipelines at scale.
  • Experience working with global distributed teams in Pune’s tech ecosystem.
  • Certifications in AWS, Azure, or GCP architecture, or Kubernetes (CKA/CKAD).