PwC - Senior Associate Forward Deployment Engineer - DevOps & AI

Job Description :Senior Associate Forward Deployment Engineer (DevOps, AI Deployment) - AI Deployment & DevOps Engineering | Forward Deployed EngineeringJob 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.- 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 FoundrySoft 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: 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 (ref:hirist.tech)