Forward Deployment Engineer (DevOps, AI Deployment)

V2 Solutions; Hyderabad; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

V2 Solutions is seeking a Senior Associate Forward Deployment Engineer (DevOps, AI Deployment) to own production deployments of AI solutions in client environments. You will design pipelines, harden AI apps for production, and ensure enterprise security and governance on AWS.

The role requires hands-on LLM deployment, scalable model serving, and mentoring engineers, with a focus on secure, regulated deployments across engagements.

Qualifications

• Substantial DevOps or platform engineering experience with ownership of production deployments.
• Deep CI/CD, Docker, and Kubernetes experience, with strong Terraform / IaC.
• Strong AWS fluency across deployment-relevant services.
• Strong grounding in identity, security, and networking, and enterprise integration.
• Solid automation skills and a habit of codifying build and run processes.
• Deep, hands-on experience deploying LLM and agentic applications to production (LLMOps), including serving, scaling, retrieval infrastructure, observability, evaluation, and responsible AI.
• Mandatory: AWS, DevOps, or GenAI certification (at least one) is required.

Responsibilities

• Own the deployment architecture for AI solutions on AWS.
• Design and own CI/CD, Infrastructure as Code, and release standards across engagements.
• Lead integration of AI solutions into legacy and regulated environments, respecting identity, security, and governance.
• Set up scalable model and agent serving, with the vector and retrieval infrastructure behind it.
• Establish observability, evaluation, and cost controls for AI workloads in production.
• Define a practical approach to security, governance, and responsible AI for deployments.
• Build reusable deployment accelerators, and mentor engineers.
• Bring field learnings and product gaps back to the wider practice.

Skills

DevOps ownership

CI/CD

Docker

Kubernetes

Terraform / IaC

AWS

Security & identity

Automation

LLMOps

Certification (AWS/GenAI)

Education

AWS/GenAI certification

Tools

AWS Bedrock

SageMaker

Lambda

ECS

EKS

Step Functions

S3

IAM

CloudWatch

Docker

Kubernetes

Terraform

Ansible

GitHub Actions

GitLab CI

Jenkins

ArgoCD

OpenTelemetry

Langfuse

Prometheus

Grafana

Job description

Senior Associate Forward Deployment Engineer (DevOps, AI Deployment) AI Deployment & DevOps Engineering | Forward Deployed Engineering Experience Required 5 to 9 years. Location: Bangalore / Hyderabad

Job Summary

A senior DevOps engineer who owns how AI solutions are deployed into a client's environment. As the technical owner for deployment, you will design pipelines and infrastructure, harden AI applications for production, and meet enterprise security and governance requirements on AWS.

Key Responsibilities

• Own the deployment architecture for AI solutions on AWS.
• Design and own CI/CD, Infrastructure as Code, and release standards across engagements.
• Lead integration of AI solutions into legacy and regulated environments, respecting identity, security, and governance.
• Set up scalable model and agent serving, with the vector and retrieval infrastructure behind it.
• Establish observability, evaluation, and cost controls for AI workloads in production.
• Define a practical approach to security, governance, and responsible AI for deployments.
• Build reusable deployment accelerators, and mentor engineers.
• Bring field learnings and product gaps back to the wider practice.

Required Qualifications

• Substantial DevOps or platform engineering experience with ownership of production deployments.
• Deep CI/CD, Docker, and Kubernetes experience, with strong Terraform / IaC.
• Strong AWS fluency across deployment-relevant services.
• Strong grounding in identity, security, and networking, and enterprise integration.
• Solid automation skills and a habit of codifying build and run processes.
• Deep, hands-on experience deploying LLM and agentic applications to production (LLMOps), including serving, scaling, retrieval infrastructure, observability, evaluation, and responsible AI.
• Mandatory: AWS, DevOps, or GenAI certification (at least one) is required.

Preferred Qualifications

• Enterprise AI platforms (Palantir Foundry, Databricks, Snowflake) and MLOps tooling at scale.
• Experience in regulated industries.
• SRE or reliability experience.
• Prior consulting, customer success, or forward-deployed work.
• AWS Certified DevOps Engineer Professional and/or AWS Certified Solutions Architect – Professional; CKA or a cloud AI/ML certification.

Technical Skills & Tools

• Cloud (AWS): Bedrock, SageMaker, Lambda, ECS, EKS, Step Functions, S3, API Gateway, IAM, CloudWatch
• Containers & IaC: Docker, Kubernetes, Helm, Terraform (modules), Ansible
• CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD (GitOps)
• AI deployment (LLMOps): model and agent serving and scaling, RAG & vector databases, evaluation, prompt versioning
• Observability & cost: OpenTelemetry, Langfuse, Prometheus, Grafana
• Security & governance: IAM, secrets management, network security, responsible-AI controls
• Scripting: Python, Go, Bash
• Good to have: MLOps at scale (MLflow, model registries, feature stores), Databricks, Snowflake, Palantir Foundry