Forward Deployment Engineer (DevOps, AI Deployment)-Senior Associate

PwC; Hyderabad, Bengaluru; Hybrid; INR 2,800,000 - 4,200,000; Full time

Job summary

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

This role is embedded with enterprise clients and focuses on end-to-end deployment ownership. The position requires hands-on LLM deployment, strong CI/CD, IaC, and cloud security experience, with a bias for scalable, observable, and compliant AI

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.

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

CI/CD

Docker

Kubernetes

Terraform / IaC

AWS deployment

LLMOps

Security & Governance

SRE

Python

Go / scripting

Tools

AWS Bedrock

SageMaker

Lambda

ECS

EKS

CloudWatch

Terraform modules

OpenTelemetry

Job description

Senior Associate Forward Deployment Engineer (DevOps, AI Deployment)

AI Deployment & DevOps Engineering | Forward Deployed Engineering

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.

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

Soft Skills & Competencies

• Takes ownership of deployment outcomes.
• Clear communication with client stakeholders.
• Mentors engineers and sets standards.
• Sound judgement on security, governance, and responsible AI.

Experience Required

6-9 years.

Reporting & Team

Embedded with an enterprise customer as the technical owner for deployment, within our Forward Deployed Engineering practice; mentors engineers on the team.

Location & Work Model

• Location: Bengaluru or Hyderabad.
• Work model: Forward-deployed and customer-facing; embedded within an enterprise client's team.
• Working hours: Overlap with client business hours (including US / EST), with occasional deployment support.