Location : Pune / Noida / Hyderabad / Bengaluru / Chennai

Position Overview :

We are seeking a Senior Cloud Engineer with deep expertise in AWS-based High-Performance Computing (HPC) and proven experience supporting Clinical Pharmacology and Pharmacometrics workloads. The incumbent will lead the design, deployment, and optimization of large-scale, secure, and compliant HPC infrastructures on AWS, enabling high-performance modeling, simulation, and computational research for global R&D teams.

Key Responsibilities :

- Architect, design, and lead implementation of HPC environments on AWS optimized for pharmacometric modeling, simulation, and data-intensive scientific workloads.

- Define and implement HPC architecture standards, cost optimization strategies, and scaling patterns across compute, storage, and data pipelines.

- Partner with Clinical Pharmacology, Pharmacometrics, and R&D IT stakeholders to translate scientific computing requirements into robust cloud solutions.

- Automate and orchestrate complex workloads for tools such as Phoenix WinNonlin, Pirana, Monolix, NONMEM, and MATLAB using AWS-native and open-source technologies.

- Lead development of Infrastructure-as-Code (IaC) frameworks using Terraform or AWS CloudFormation for reproducible and auditable infrastructure provisioning.

- Drive CI/CD pipeline implementation for model execution and environment deployment.

- Ensure adherence to 21 CFR Part 11, GxP, and organizational data security and compliance standards.

- Provide technical mentorship to junior engineers and guide cross-functional teams in best practices for HPC workload management and cloud optimization.

- Conduct performance benchmarking, cost analysis, and scalability assessments to continuously improve HPC infrastructure.

Required Technical Skills :

- Cloud Platforms : Expert-level proficiency in AWS (EC2, Batch, ParallelCluster, FSx, S3, CloudFormation, Lambda).

- High Performance Computing : HPC cluster architecture, scheduling (SLURM / AWS Batch), parallel and distributed computing, containerization (Docker, Singularity).

- Infrastructure-as-Code (IaC) : Terraform, AWS CloudFormation.

- Scripting & Automation : Advanced skills in Python, Bash, and PowerShell.

- DevOps & CI/CD : Jenkins, GitHub Actions, or similar tools for automating environment deployment.

- OS & Networking : Linux (RHEL/Ubuntu), IAM, VPC design, network security, VPN, and hybrid connectivity (Direct Connect).

- Monitoring & Optimization : AWS CloudWatch, CloudTrail, Cost Explorer, and cost governance best practices.

- Data Storage : Experience with S3 lifecycle management, FSx for Lustre, EFS, and data caching strategies for HPC workloads.

- Experience integrating and supporting modeling and simulation tools - Phoenix WinNonlin, Pirana, Monolix, NONMEM, MATLAB.

- Understanding of clinical data standards (CDISC, SDTM, ADaM) and workflows in Clinical Pharmacology / Pharmacometrics.

- Familiarity with data visualization and analytics tools (Spotfire, R Shiny, Tableau).

- Experience with workflow management systems (Nextflow, Airflow, Snakemake).

- Exposure to container orchestration (Kubernetes / AWS EKS).

- Prior experience in a regulated life sciences IT or pharmaceutical R&D computing environment.

Domain Experience (Mandatory) :

- In-depth understanding of Clinical Pharmacology and Pharmacometrics workflows, including PK/PD modeling, parameter estimation, and simulation processes.

- Experience collaborating with scientists and modelers to support computational R&D workloads in a regulated environment.

Education :

- Bachelor's or Master's degree in Computer Science, Computational Sciences, or a related field.

- Additional certifications in Clinical Pharmacology, AWS Certifications: AWS Certified Solutions Architect - Professional or AWS Certified Advanced Networking - Specialty.