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DevOps Engineer_AI ( ALMops & LLMops) Manager

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Onsite

DevOps Engineer_AI ( ALMops & LLMops) Manager

PwC

DevOps Engineer_AI ( ALMops & LLMops) Manager

Skills

Consulting ITAWS LambdaSnowflakeDatabricksGitLabAIAWSGitHubKubernetesComplianceTerraformAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

21 September 2026

What they need


Greetings from Pwc!

Role- Devops Engineer( Mandatory skills AWS, AI , Kubernates)Certification mandatory**

Location- Hyderabad & Bangalore

Experience Required (9--13years)

Aws or Azure or Devop's Certification mandatory

If interested Share cv on [email protected] or WhatsApp on 6304776536 with below details

Total experience-

Relevant Experience-

Current location-

Preferred location-

Current CTC-

Expected CTC

Manager Forward Deployment Engineer (DevOps, AI Deployment)

AI Deployment & DevOps Engineering | Forward Deployed Engineering

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.

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.

Experience Required

9–12 years, including team and delivery leadership.

Reporting & Team

Leads a team of forward-deployed engineers embedded with customers, within our Forward Deployed Engineering practice.

Location & Work Model

  • Location: Anywhere in India, with a preference for 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.

  • Seniority Level
    Mid-Senior level

  • Industry

  • IT Services and IT Consulting

  • Employment Type
    Full-time

  • Job Functions

  • Engineering

  • Skills

  • Amazon Web Services (AWS)

  • Kubernetes

  • Continuous Integration and Continuous Delivery (CI/CD)

  • Artificial Intelligence (AI)

  • Agentic Automation

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