Applied AI / Automation DevOps Engineer (AWS) — Amgen · Hyderabad

About the role

Build automation and DevOps pipelines for Amgen's Applied AI platform — Python-led automation, AWS infrastructure-as-code, CI/CD for ML models, with full GxP / Computer System Validation rigor.

About this role and the team at Amgen. Build automation and DevOps pipelines for Amgen's Applied AI platform — Python-led automation, AWS infrastructure-as-code, CI/CD for ML models, with full GxP / Computer System Validation rigor. This listing on cloudsoftsol.com is curated for engineers in India who are actively interviewing for senior cloud and DevOps roles. If you are seeking a multi-year career platform rather than a stop-gap, this listing rewards depth — read the responsibilities and requirements below carefully and tailor your application to the specifics. We do not charge candidates a fee for placement assistance; companies sponsor our involvement.

Responsibilities

Build the automation backbone for Amgen's Applied AI platform: Python-based orchestration that ties together SageMaker training jobs, Snowflake / Databricks feature pipelines, REST APIs published by data-product teams, and the regulated audit trail required by Computer System Validation (CSV). Design and own CI/CD pipelines (GitHub Actions plus Jenkins for legacy components) that build, test, scan and deploy model containers and the supporting infrastructure into AWS — with traceability records that survive an FDA inspection. Maintain Amgen's GxP-compliant Terraform module library — VPC, IAM, EKS, S3, KMS, RDS Aurora and SageMaker — so that any team can spin up a validated environment from a single backstage template. Automate operational workflows: model retraining triggers based on data drift, scheduled regulatory report generation via Step Functions, and Ansible-driven configuration management for the few remaining EC2-hosted services. Operate observability through Splunk for security audit trails, CloudWatch + Prometheus for application metrics, and PagerDuty for on-call. Tune alerting so that GxP-impacting incidents are escalated within minutes, while non-impacting noise is suppressed. Partner with the Quality Assurance and Regulatory Affairs teams to deliver pipeline change-records, IQ / OQ / PQ artefacts, and periodic-review documentation. Treat the documentation pipeline as code, generated automatically wherever possible. Lead at least one major automation initiative per year — for example, replacing manual deployment runbooks with self-service backstage actions, or migrating a legacy Jenkins farm onto GitHub Actions self-hosted runners. Mentor analysts and graduate engineers joining the platform team, run brown-bag sessions on AWS and Python best practices, and represent the Hyderabad hub in global architecture-review boards.

Requirements & qualifications

4-9 years total experience with 3+ years building production automation in Python on AWS. Hands-on with at least two of: SageMaker, Snowflake, Databricks, Step Functions, Lambda. Deep familiarity with the rest of the AWS catalogue (S3, IAM, KMS, EKS, RDS, CloudWatch). Proven CI/CD ownership using GitHub Actions and / or Jenkins, including reusable workflows, secret management, and self-hosted runner farms. Strong Terraform skills: writing modules, managing remote state per environment, and reviewing other engineers' plans for cost and security implications. Working understanding of GxP / Computer System Validation, FDA 21 CFR Part 11, GAMP-5 categorisation, or comparable regulated-software frameworks. Excellent written communication — you will produce change-records and validation artefacts that go to auditors and regulators. Bachelor's or higher in Computer Science, Engineering, or a numerate science. AWS or HashiCorp certifications a plus.

Why this role in 2026

Amgen's Hyderabad capability centre is one of the company's three global engineering hubs and houses the Applied AI platform team that powers clinical and manufacturing decisions worth hundreds of millions of dollars. The role is rare — a true Python + AWS + MLOps + regulated-software combination — and the people who own it tend to leverage it into senior platform-engineering or pharma-tech leadership positions within 4-6 years.

Application tips

Apply via the Amgen careers portal (link below) and follow up with a polished LinkedIn message to the recruiter once your application is in. Lead with concrete examples of GxP or comparable regulated-software work — auditors, change records, validated environments — even if you label it differently in your current role.

Interview preparation

Five rounds typical: recruiter screen, Python + AWS technical phone screen, deeper technical loop with two engineers (system design + code review), a Quality / Regulatory partner round on validation discipline, and a values round with a director. Practice STAR stories around CI/CD failures, audit findings and how you closed them, and any rollback you owned end-to-end.

Career growth

Inside Amgen: Senior Applied AI Engineer (year 1-2), Principal Engineer or Lead Architect (year 3-4), Director of Platform / MLOps (year 5+). Many engineers also rotate into the Manufacturing IT or Clinical Data Sciences platform teams.