Job Description

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

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AI Deployment & DevOps Engineering | Forward Deployed Engineering

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Experience Required

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6–9 years.

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Location: Bangalore / Hyderabad

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Job Summary

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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.

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Key Responsibilities

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- Own the deployment architecture for AI solutions on AWS.
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- Design and own CI/CD, Infrastructure as Code, and release standards across engagements.
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- Lead integration of AI solutions into legacy and regulated environments, respecting identity, security, and governance.
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- Set up scalable model and agent serving, with the vector and retrieval infrastructure behind it.
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- Establish observability, evaluation, and cost controls for AI workloads in production.
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- Define a practical approach to security, governance, and responsible AI for deployments.
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- Build reusable deployment accelerators, and mentor engineers.
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- Bring field learnings and product gaps back to the wider practice.
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Required Qualifications

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- Substantial DevOps or platform engineering experience with ownership of production deployments.
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- Deep CI/CD, Docker, and Kubernetes experience, with solid Terraform / IaC.
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- Strong AWS fluency across deployment-relevant services.
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- Strong grounding in identity, security,



and networking, and enterprise integration.
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- Solid automation skills and a habit of codifying build and run processes.
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- Deep, hands-on experience deploying LLM and agentic applications to production (LLMOps), including serving, scaling, retrieval infrastructure, observability, evaluation, and responsible AI.
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- Mandatory: AWS, DevOps, or GenAI certification (at least one) is required.
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Preferred Qualifications

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- Enterprise AI platforms (Palantir Foundry, Databricks, Snowflake) and MLOps tooling at scale.
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- Experience in regulated industries.
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- SRE or reliability experience.
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- Prior consulting, customer success, or forward-deployed work.
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- AWS Certified DevOps Engineer – Professional and/or AWS Certified Solutions Architect – Professional; CKA or a cloud AI/ML certification.
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Technical Skills & Tools

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- Cloud (AWS): Bedrock, SageMaker, Lambda, ECS, EKS, Step Functions, S3, API Gateway, IAM, CloudWatch
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- Containers & IaC: Docker, Kubernetes, Helm, Terraform (modules), Ansible
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- CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD (GitOps)
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- AI deployment (LLMOps): model and agent serving and scaling, RAG & vector databases, evaluation, prompt versioning
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- Observability & cost: OpenTelemetry, Langfuse, Prometheus, Grafana
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- Security & governance: IAM, secrets management, network security, responsible-AI controls
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- Scripting: Python, Go, Bash
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- Good to have: MLOps at scale (MLflow, model registries, feature stores), Databricks, Snowflake, Palantir Foundry
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📌 Forward Deployment Engineer (DevOps, AI Deployment) (Bengaluru)
🏢 PwC Acceleration Centers
📍 Bengaluru