Job Description:
About the Role
We're looking for an AI DevOps Engineer who lives at the intersection of production AI/ML infrastructure and creative technology. You'll own the deployment, scaling, and reliability of our generative AI systems — RAG pipelines, multi-agent workflows, multimodal and vision models — across all three major clouds. Just as importantly, you understand the creative side: you can plug AI into real production pipelines built on tools like After Effects and Figma, and you speak the language of designers, animators, and media teams.
This is a builder role for someone who's equally comfortable writing Terraform and reasoning about a vector retrieval pipeline, and who gets genuinely excited when AI infrastructure ships something creative into the world.
What You'll Do
- Design, build, and operate CI/CD and MLOps/LLMOps pipelines for deploying AI models and services across Azure, GCP, and AWS.
- Deploy and scale RAG systems end to end — embeddings, vector databases, retrieval and re-ranking pipelines, and evaluation.
- Stand up and operate multi-agent orchestration frameworks (e.g. LangGraph, CrewAI, AutoGen, or similar) in production, including tool integration, state management, and observability.
- Integrate and serve multimodal, vision, and computer vision capabilities — vision APIs, image/video understanding, and CV model inference.
- Own infrastructure-as-code, containerization, and orchestration (Terraform, Docker, Kubernetes) and GPU-backed model serving.
- Build monitoring, logging, cost tracking, and performance optimization for GenAI and LLM workloads.
- Partner with creative and design teams to embed AI into creative production pipelines — automating and extending workflows in tools like Adobe After Effects and Figma.
- Champion reliability, security, and reproducibility across the AI stack.
Required Qualifications
- 4–7 years of experience in DevOps / LLMOps / Platform Engineering with an GENAI & ML focus, including a track record of shipping systems to production.
- Hands-on deployment experience across at least two of Azure, GCP, and AWS (all three strongly preferred).
- Strong with Docker, Kubernetes, and Terraform (or equivalent IaC).
- Practical experience building RAG pipelines and working with vector databases and embeddings.
- Experience with multi-agent orchestration and modern LLM / agent frameworks.
- Familiarity with vision APIs and computer vision — integrating and serving vision or multimodal models.
- Strong scripting and automation skills in Python (plus comfort with shell / another language).
- CI/CD, observability, and infrastructure cost-management fundamentals.
Good to Have
- Background in media, creative AI, animation, or design production.
- Hands-on with Adobe After Effects (AFx) and Figma — including scripting, plugins, or workflow automation.
- Experience with generative media models (image, video, audio, or 3D generation).
- Understanding of creative production pipelines and how to integrate AI into them.
- Exposure to fine-tuning, model evaluation, or prompt engineering at scale.
What Success Looks Like
In your first few months, you'll have deployed at least one GenAI service to production across our cloud environment, made it observable and cost-efficient, and worked directly with a creative team to ship an AI-powered feature into their workflow.
Location:
DGS India - Gurugram - Golf View Corporate TowersBrand:
MerkleTime Type:
Full timeContract Type:
PermanentSkills Required
- 4–7 years of experience in DevOps, LLMOps, or Platform Engineering with a GenAI and ML focus
- Track record of shipping AI/ML systems to production
- Hands-on deployment experience across at least two of Azure, GCP, and AWS
- Strong experience with Docker, Kubernetes, and Terraform or equivalent infrastructure as code
- Practical experience building RAG pipelines and working with vector databases and embeddings
- Experience with multi-agent orchestration and modern LLM or agent frameworks
- Familiarity with vision APIs and computer vision, including integrating and serving vision or multimodal models
- Strong Python scripting and automation skills
- Comfort with shell scripting or another programming language
- Experience with CI/CD, observability, and infrastructure cost management
- Background in media, creative AI, animation, or design production
- Hands-on experience with Adobe After Effects and Figma, including scripting, plugins, or workflow automation
- Experience with generative media models for image, video, audio, or 3D generation
- Understanding of creative production pipelines and AI integration
- Exposure to fine-tuning, model evaluation, or prompt engineering at scale
dentsu Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dentsu and has not been reviewed or approved by dentsu.
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Parental & Family Support — Paid parental leave at full pay and caregiver supports (including backup care) are emphasized as standout elements. Feedback suggests family-oriented benefits are a strong part of the package.
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Leave & Time Off Breadth — Flexible or unlimited PTO, extensive paid holidays, and a year-end office closure are established components. Feedback suggests time-off policies are generous and add meaningful flexibility.
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Retirement Support — A large, established 401(k) plan with employer matching is clearly documented. Feedback suggests retirement benefits feel competitive and straightforward.
dentsu Insights
What We Do
We are dentsu. We team together to help brands predict and plan for disruptive future opportunities and create new paths to growth in the sustainable economy. We know people better than anyone else and we use those insights to connect brand, content, commerce and experience, underpinned by modern creativity. We are the network designed for what’s next
