About the Role

We are seeking a proactive AI engineer with a robust 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).

📌 AI Automation Lead (Maharashtra)
🏢 Cephas Consultancy Services Private
📍 Maharashtra