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

AI Deployment & DevOps Engineering | Forward Deployed Engineering

Location: Bangalore / Hyderabad

Experience Required

6 – 9 years.

Job Summary 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.

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. - Solid 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.

📌 Forward Deployment Engineer (DevOps, AI Deployment) (Bengaluru)
🏢 PwC Acceleration Centers
📍 Bengaluru