DevOps Engineer – AI/ML, Agentic Workflows

🚀 DevOps Engineer – Multi-Agent AI Platform

Bim Digital / AR Sync AI | Remote (3 Months) → Hyderabad**

Multi-Agentic AI Automation Platform

DevOps Engineer

Strong freshers with excellent skills and deep interest in DevOps & cloud engineering are also encouraged to apply.

Role: DevOps Engineer – AI/Multi-Agent Platform

Location:

Type:

Experience:

Role Overview

You will work on the infrastructure that powers our AI agents, vector databases, LLM pipelines, and backend microservices.

This includes CI/CD, Kubernetes, cloud automation, monitoring, and deployments for enterprise clients.

Core ResponsibilitiesCloud & Infrastructure

• Deploy and manage cloud environments (AWS / Azure / GCP)
• Manage computing resources for

  LLM inference

  , RAG pipelines, agent orchestration
• Set up vector DB infrastructure (Chroma, Pinecone, Weaviate, pgvector)
• Support deployments of Python microservices and backend APIs

CI/CD & Automation

• Create and maintain CI/CD pipelines (GitHub Actions / GitLab / Azure DevOps)
• Automate testing, building, containerization, and deployments
• Implement best practices for code quality and release cycles

Containerization & Orchestration

• Build Docker images for various microservices
• Deploy and manage Kubernetes clusters (EKS / AKS / GKE)
• Set up autoscaling, resource allocation, service mesh, and ingress

Monitoring, Logging & Reliability

• Set up monitoring dashboards (Prometheus, Grafana, Datadog, CloudWatch)
• Implement application logs, distributed tracing, and alerting
• Ensure reliability and uptime of agent workflows and API services

Security & Compliance

• Manage IAM, RBAC, VPN, VPC, SSL, and environment security
• Implement secrets management and zero-trust practices
• Support on-prem or hybrid deployments for enterprise clients

Dev Environment Management

• Manage staging, UAT, and production environments
• Help developers with environment provisioning, testing, and debugging
• Optimize resource usage for LLM-heavy workloads

Required Skills

• Basic to strong experience with:
• AWS / Azure / GCP
• Linux & Shell scripting
• Docker & Docker Compose
• Git & CI/CD concepts
• Understanding or exposure to:
• Kubernetes
• Networking basics (DNS, SSL, Load Balancers, VPC)
• Infrastructure as Code (Terraform / CloudFormation / Pulumi)

Strong Freshers Are Preferred If They Have:

• Strong knowledge of Linux, networking & cloud fundamentals
• Hands-on mini-projects in AWS/Azure/GCP
• Docker knowledge and basic Kubernetes understanding
• GitHub portfolio with DevOps or cloud projects
• Fast learning ability and strong troubleshooting mindset

Good to Have

• Experience deploying AI/ML/LLM workloads
• Exposure to vector databases (Chroma, Pinecone, pgvector)
• SRE concepts — observability, SLAs, root-cause analysis
• Experience with enterprise deployments (VPNs, on-prem, hybrid cloud)

Who You Are

• You love automation and building scalable infrastructure
• You are proactive, curious, and take ownership
• Comfortable in a fast-paced startup environment
• Able to collaborate with AI engineers, backend developers, and QA
• Excited about supporting AI/LLM systems at scale

What We Offer

• Work on a global

  multi-agent AI automation platform

• Exposure to real-world LLM infrastructure and enterprise deployments
• Fast growth into

  DevOps Lead / SRE Engineer

  roles
• Competitive salary + performance bonuses
• High learning curve with real engineering challenges

Apply Now

Send your resume + GitHub/portfolio to:

@bimbasree.in