DevOps Engineer – AI/ML, Agentic Workflows

7 years

0 Lacs

Posted:3 weeks ago| Platform: Linkedin logo

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Job Description

🚀 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


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