Job Type: Full-time

DevOps Engineer I – AWS & AIPune, Fulltime, HybridKey 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 DevOps Engineer I – AWS & AI- 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 fast experimentation and reliable deploymentRequired Qualifications- 3 - 5 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- Solid 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 environmentsPreferred 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- Seniority Level- Mid-Senior level- Industry- IT Services and IT Consulting- Employment Type- Full-time

📌 DevOps Engineer I – AWS & AI (Nagpur)
🏢 Panzer Technologies
📍 Nagpur