LLM Integration & CI/CD Engineer-- Senior Associate-AI Managed Services - Consult

PwC Acceleration Center India

Bengaluru

On-site

INR 3,000,000 - 5,000,000

Full time

8 days ago

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Job summary

PwC Acceleration Center India seeks an LLM Integration & CI/CD Engineer—Senior Associate to deliver AI-driven Managed Services. You will own deployment architectures on AWS, build robust CI/CD pipelines, and mentor engineers within a forward-deployed enterprise setting.

Roles include integrating LLMs, ensuring security/governance, and partnering with clients to meet timelines while maintaining quality standards. 6–9 years of experience preferred.

Qualifications

Extensive DevOps ownership and production deployments.
Strong AWS fluency across deployment-relevant services.
Deep LLM/agent deployments (LLMOps) and observability.

Responsibilities

Own deployment architecture for AI solutions on AWS.
Design CI/CD, Infrastructure as Code, and release standards across engagements.
Lead integration of AI into legacy/reg environments with governance.

Skills

DevOps ownership

CI/CD

AWS fluency

Security governance

LLMOps

Mentoring engineers

Stakeholder communication

Education

Bachelor's degree in a related field

Tools

Docker

Kubernetes

Terraform

Ansible

GitHub Actions

GitLab CI

Jenkins

ArgoCD

OpenTelemetry

Langfuse

Prometheus

Job description

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As an LLM Integration & CI/CD Engineer-- Senior Associate-AI Managed Services - Consult, you will play a pivotal role in delivering client-focused solutions within our Managed Services practice. You will leverage your skills to integrate large language models and streamline continuous integration and continuous deployment processes, enhancing the efficiency and effectiveness of AI-driven services. As a Senior Associate, you will focus on building meaningful client connections and navigating complex situations to deliver quality work. You will guide and mentor junior team members, fostering their growth while developing your own personal brand and technical skills.

In this role at PwC Acceleration Center India, you will collaborate within our Data, Analytics & AI Managed Services network, contributing to innovative solutions that address client needs. Your work will involve analyzing complex concepts and interpreting data to inform insights and recommendations. You will be expected to anticipate the needs of your teams and clients, embracing increased ambiguity and using these moments as opportunities to grow. This position offers a unique chance to deepen your understanding of the business context and how it is evolving, while maintaining professional and technical standards.

Responsibilities

Designing and implementing automation frameworks to enhance operational efficiency
Managing continuous integration and continuous deployment (CI/CD) pipelines to streamline project delivery
Developing and optimizing business process automation solutions to improve service delivery
Collaborating with stakeholders to identify and address operational performance challenges
Utilizing analytical thinking to troubleshoot performance issues and propose innovative solutions
Leading efforts in process improvement and optimization to achieve operational excellence
Planning and executing deliverables to meet project timelines and quality standards
Engaging in stakeholder management to align project objectives with client expectations
Overseeing service level management to maintain consistent service quality
Conducting risk documentation and operational risk management to mitigate potential issues

What You Must Have

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: 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.

What Sets You Apart