Forward Deployment Engineer Devops and AI Development

PwC; Hyderabad, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

PwC is seeking a seasoned Associate Forward Deployment Engineer (DevOps, AI Deployment) to pilot AI solutions into production on AWS. You will join a client team to move AI applications from prototype to secure, scalable deployments with strong CI/CD, containers, and infrastructure automation.

Responsibilities include packaging AI/LLM apps for AWS Bedrock, building CI/CD pipelines, containerizing with Docker, provisioning IaC with Terraform, and ensuring observability and cost tracking.

Qualifications

• Proven DevOps experience shipping to production.
• Strong CI/CD and release-automation experience.
• Hands-on production experience with Docker and Kubernetes.
• Infrastructure as Code experience and strong AWS fluency.
• Scripting ability for automation (Python and/or Bash).
• Ability to integrate into a client's identity, security, and networking setup.
• A real understanding of how AI and LLM applications are deployed and run in production, including model serving and RAG/vector infrastructure.
• AWS Certified Solutions Architect – Associate or AWS Certified DevOps Engineer – Associate.

Responsibilities

• Package and deploy AI/LLM applications and agent workflows onto the client's AWS infrastructure.
• Build and maintain CI/CD pipelines that ship AI services safely and repeatably.
• Containerise services with Docker and run them on Kubernetes.
• Provision infrastructure as code with Terraform, integrating the required identity, security, and networking.
• Set up model and application serving, including AWS Bedrock integrations and vector database infrastructure.
• Add observability and cost tracking for AI workloads.
• Integrate AI solutions into existing legacy systems and regulated data environments.
• Automate repetitive deployment and operations tasks.
• Collaborate with client engineers over Teams, Slack, and email, and keep deployment runbooks current.

Skills

DevOps

CI/CD

Docker

Kubernetes

Terraform

AWS

Python/Bash scripting

IaC

Security/Identity integration

AI/LLM deployment understanding

Education

AWS Certified Solutions Architect – Associate

AWS Certified DevOps Engineer – Associate

Tools

GitHub Actions

GitLab CI

Jenkins

ArgoCD

Terraform

CloudFormation

Job description

Associate Forward Deployment Engineer (DevOps, AI Deployment)

AI Deployment & DevOps Engineering | Forward Deployed Engineering

Location: Bangalore / Hyderabad

Experience Required

3 –6 years.

Job Summary

A DevOps engineer focused on getting AI solutions into real production. Embedded within an enterprise client's team, you will take AI applications from prototype to reliable, secure production on AWS, using strong CI/CD, containerisation, and infrastructure automation.

Key Responsibilities

• Package and deploy AI/LLM applications and agent workflows onto the client's AWS infrastructure.
• Build and maintain CI/CD pipelines that ship AI services safely and repeatably.
• Containerise services with Docker and run them on Kubernetes.
• Provision infrastructure as code with Terraform, integrating the required identity, security, and networking.
• Set up model and application serving, including AWS Bedrock integrations and vector database infrastructure.
• Add observability and cost tracking for AI workloads.
• Integrate AI solutions into existing legacy systems and regulated data environments.
• Automate repetitive deployment and operations tasks.
• Collaborate with client engineers over Teams, Slack, and email, and keep deployment runbooks current.

Required Qualifications

• Proven DevOps, platform, or deployment engineering experience shipping to production.
• Strong CI/CD and release-automation experience.
• Hands‑on production experience with Docker and Kubernetes.
• Infrastructure as Code experience and strong AWS fluency.
• Scripting ability for automation (Python and/or Bash).
• Ability to integrate into a client's existing identity, security, and networking setup.
• A real understanding of how AI and LLM applications are deployed and run in production, including model serving and RAG/vector infrastructure.
• AWS Certified Solutions Architect – Associate or AWS Certified DevOps Engineer – Associate.

Preferred Qualifications

• Deploying inside regulated environments with governance and change‑management overhead.
• Enterprise AI or data platforms such as Databricks, Snowflake, or Palantir Foundry.
• MLOps tooling (MLflow, model registries, feature stores).
• Some SRE or reliability experience.
• Prior customer‑facing or forward‑deployed work.
• Certified Kubernetes Administrator (CKA) or a Terraform Associate certification.

Technical Skills & Tools

• Cloud (AWS): Bedrock, SageMaker, Lambda, ECS, EKS, Step Functions, S3, API Gateway, IAM, CloudWatch
• Containers & IaC: Docker, Kubernetes, Helm, Terraform, Ansible, CloudFormation
• CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD
• AI deployment: LLM/agent serving, inference endpoints, RAG infrastructure, vector databases (Pinecone, pgvector, Weaviate, Qdrant, OpenSearch)
• Observability & cost: OpenTelemetry, Langfuse, Prometheus, Grafana, CloudWatch
• Security & networking: IAM, secrets management, VPC and network configuration
• Scripting: Python, Bash, Git
• Good to have: MLOps (MLflow, model registries, feature stores), Databricks, Snowflake, Palantir Foundry