DevOps Engineer II – AWS & AI

Pune, Fulltime, Hybrid Key Responsibilities • Own and maintain production AWS infrastructure with high availability, fault tolerance, and proactive monitoring

- Build and manage scalable cloud infrastructure using Terraform and Ansible on AWS
- Deploy and manage AI/LLM workloads, vector databases, and model inference pipelines
- Design and maintain secure CI/CD pipelines for microservices and AI/ML systems
- Implement security best practices including IAM policies, secrets management, and vulnerability scanning
- Set up observability and monitoring for both system and AI metrics (latency, throughput, cost, usage)
- Optimize cloud costs, particularly for GPU-backed and compute-intensive AI workloads
- Manage VPC networking, DNS, load balancing, and secure connectivity across AWS environments
- Collaborate closely with AI/ML engineers and product teams to ensure infrastructure supports quick experimentation and reliable deployment Required Qualifications • 5-7 years of hands-on experience in DevOps, SRE, or cloud infrastructure roles
- Proven experience working at a product-based company with fast-paced engineering teams
- Strong hands-on expertise with core AWS services: EKS, ECS/Fargate, EC2, S3, RDS, SageMaker, Lambda, VPC, and CloudFront




- Experience deploying and managing AI/LLM workloads, vector databases (e.g., Pinecone, Weaviate, pgvector), and LLM APIs (OpenAI, Bedrock, etc.)
- Solid expertise in Docker, Kubernetes (EKS), Terraform, and Ansible
- Proficiency in Python scripting for automation, tooling, and infrastructure workflows — this is a mandatory requirement
- Strong understanding of Linux/Unix systems, preferably Ubuntu
- Sound knowledge of networking fundamentals, security architecture, and IAM principles on AWS • Demonstrated experience delivering AI projects in production — not just experimental or PoC environments Preferred Skills
- Experience with LLMOps practices — prompt versioning, model monitoring, RAG pipelines, and inference optimization
- Familiarity with AI/ML frameworks (SageMaker Pipelines, MLflow, Kubeflow) and model serving patterns
- Hands-on experience with observability tools such as Prometheus, Grafana, CloudWatch, or OpenTelemetry
- Automation-first mindset with the ability to work across complex distributed systems
- Exposure to AWS Bedrock, Rekognition, Comprehend, or other managed AI/ML services
- Strong debugging, performance tuning, and root cause analysis skills

📌 DevOps Engineer II – AWS & AI (Pune)
🏢 Panzer Technologies
📍 Pune