Forward Deployment Engineer (DevOps, AI Deployment)

PwC; Hyderabad, Bengaluru; Hybrid; INR 3,000,000 - 6,000,000; Full time

Job summary

PwC in India is seeking a Senior Associate Forward Deployment Engineer (DevOps, AI Deployment) to own how AI solutions are deployed into client environments. You will design pipelines and infrastructure, harden AI apps for production, and meet enterprise security and governance on AWS.

Location is Bangalore or Hyderabad with hands-on deployment ownership. You will lead CI/CD, IaC, and release standards, integrate AI into regulated landscapes, and build scalable model serving with observability

Qualifications

• Extensive production deployment ownership in DevOps or platform engineering.
• Strong experience with CI/CD, Docker, Kubernetes, and IaC (Terraform).
• Fluent AWS capability across deployment services.
• Solid knowledge of identity, security, networking for enterprise environments.
• Proficient automation and codifying build/run processes.
• Hands-on experience deploying LLM/agentic apps (LLMOps) to prod.
• Certification in AWS, DevOps, or GenAI is required.

Responsibilities

• Own deployment architecture for AI solutions on AWS.
• Design and own CI/CD, IaC, and release standards.
• Lead integration of AI into legacy/regulatory environments with governance.
• Set up scalable model serving and retrieval infrastructure.
• Establish observability and cost controls for AI workloads.
• Define security and responsible AI practices for deployments.
• Build reusable deployment accelerators and mentor engineers.
• Capture field learnings and feed product improvements.

Skills

DevOps

Platform engineering

CI/CD

Docker

Kubernetes

Terraform / IaC

AWS

Security

Networking

Automation

LLMOps

LLM deployment

Certification

Tools

GitHub Actions

GitLab CI

Jenkins

ArgoCD

OpenTelemetry

Langfuse

Prometheus

Grafana

SageMaker

Bedrock

ECS

EKS

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