Manager _Forward Deployment Engineer , DevOps, AI Deployment

PwC; Hyderabad, Bengaluru; Hybrid; INR 3,000,000 - 6,500,000; Full time

Job summary

PwC is seeking an experienced Manager Forward Deployment Engineer to lead the end-to-end deployment of AI solutions in enterprise environments on AWS. You will own delivery, standards, and key customer relationships, guiding secure, scalable AI applications from development to production.

The role requires strong leadership, deep AWS/Kubernetes experience, and a proven track record in implementing CI/CD and IaC pipelines at scale within regulated industries.

Qualifications

• Extensive DevOps or platform engineering experience with team leadership.
• Depth in AWS, Kubernetes, CI/CD, and IaC.
• Enterprise integration experience with security, identity, governance constraints.
• Proven ownership of delivery outcomes and senior customer relationships.
• Strategy for productionising AI at scale (LLMOps/MLOps) with responsible AI, backed by delivery.
• Strong leadership and communication; decisive under pressure.
• Mandatory: AWS, DevOps, or GenAI certification (at least one).

Responsibilities

• Own the delivery of AI deployment work across accounts, including scope, quality, timelines, and standards.
• Set direction and standards for CI/CD, IaC, cloud architecture, security, and MLOps/LLMOps.
• Lead the responsible integration of AI solutions into legacy and regulated enterprise environments at scale.
• Act as senior escalation and decision-maker on complex deployments.
• Build reusable accelerators and patterns to raise deployment quality across the practice.
• Lead and grow the team through hiring, coaching, and development.
• Own senior customer relationships and communicate progress, risks, and value.
• Surface delivery friction and product gaps to leadership as structured field intelligence.

Skills

DevOps leadership

Delivery ownership

AWS

Kubernetes

CI/CD

LLMOps

Security & governance

Communication

Tools

AWS

Kubernetes

GitHub Actions

GitLab CI

ArgoCD

Terraform

Palantir Foundry

Databricks

Snowflake

MLflow

Job description

Manager Forward Deployment Engineer (DevOps, AI Deployment)

AI Deployment & DevOps Engineering | Forward Deployed Engineering

Experience Required

9 to 16 years, including team and delivery leadership.

Job Summary

An engineering leader who owns how AI solutions are deployed into enterprise environments across a set of accounts. You will own delivery, standards, and the customer relationship, and set the direction for building, securing, and operating AI applications in production on AWS.

Key Responsibilities

• Own the delivery of AI deployment work across your accounts, including scope, quality, timelines, and standards.
• Set direction and standards for CI/CD, Infrastructure as Code, cloud architecture, security, and MLOps/LLMOps.
• Lead the responsible integration of AI solutions into legacy and regulated enterprise environments at scale.
• Act as senior escalation and decision-maker on complex or high-stakes deployments.
• Build reusable accelerators and patterns that raise deployment quality across the practice.
• Build, lead, and grow the team through hiring, coaching, and development.
• Own senior customer relationships and communicate progress, risks, and value.
• Surface delivery friction and product gaps to leadership as structured field intelligence.

Required Qualifications

• Extensive DevOps or platform engineering experience, including leading teams and owning delivery at scale.
• Current depth in AWS, Kubernetes, CI/CD, and Infrastructure as Code.
• Proven enterprise integration experience with security, identity, and governance constraints.
• Proven ownership of delivery outcomes and senior customer relationships.
• A clear strategy for productionising AI at scale (LLMOps/MLOps), including responsible AI, backed by delivery experience.
• Strong leadership and communication skills; decisive under pressure.
• Mandatory: AWS, DevOps, or GenAI certification (at least one) is required.

Preferred Qualifications

• AWS enterprise-scale architecture experience.
• Enterprise AI and data platforms (Palantir Foundry, Databricks, Snowflake).
• A background in consulting or managed services.
• Experience in regulated industries.
• A leadership or delivery certification (e.g., PMP, SAFe).
• AWS Certified Solutions Architect Professional and/or AWS Certified DevOps Engineer Professional.

Technical Skills & Tools

• Cloud & platform: AWS (Bedrock, SageMaker, EKS, Lambda, IAM), Kubernetes
• Delivery & IaC: CI/CD (GitHub Actions, GitLab CI, ArgoCD), Terraform
• AI productionisation: LLMOps / MLOps, model serving, evaluation, responsible AI, governance
• Security & compliance: IAM, secrets management, network security, data governance
• Good to have: Enterprise AI and data platforms (Palantir Foundry, Databricks, Snowflake), MLflow

Soft Skills & Competencies

• Leadership of both a team and a customer relationship.
• Stakeholder and customer management.
• Decisive under pressure.
• Coaching and people development.