Principal AI/DS Platform Engineer / Architect

GenZ Talent; Lahore; A distancia; PKR 2.232.000 - 4.464.000; Jornada completa

Descripción de la vacante

GenZ Talent is seeking a Principal AI/DS Platform Engineer / Architect to lead the architecture and design of enterprise AI/ML platforms for a healthcare client. You will drive AWS-based AI/ML infrastructure, including Bedrock, SageMaker, EKS, Lambda, and S3, with a focus on scalable, secure, production-ready systems.

The role requires 8+ years of experience designing production-grade AI/ML architectures, strong Python skills, and expertise in MLOps/LLMOps, time-zone aligned with US hours.

Formación

• 8+ years hands-on AI/ML platform engineering or architecture experience.
• Proven track record designing production AI/ML platforms.
• Strong AWS expertise (Bedrock, SageMaker, EKS, Lambda, S3, IAM, VPC).
• Experience with OpenSearch or Kendra; LLMs, RAG, embeddings; MLOps/LLMOps.

Responsabilidades

• Lead end-to-end architecture and design of enterprise AI/ML platforms on AWS.
• Design scalable, secure, production-ready AI/ML infra.
• Architect RAG systems (embeddings, vector search, hybrid search, re-ranking).
• Develop LLM gateways, guardrails, evaluation and prompt management.

Conocimientos

AWS architecture

Python

LLMs

MLOps

Statistical modeling

Herramientas

AWS Bedrock

SageMaker

EKS

Lambda

S3

OpenSearch

Kendra

Terraform

CDK

Descripción del empleo

Principal AI/DS Platform Engineer / Architect

Location: Remote (Pakistan)
Salary: PKR 200,000 – 400,000 per month, depending on experience
Experience: 8+ years
Working Hours: US Time Zone
Employment Type: Permanent after 2-month probation

About the Role

We are looking for an experienced Principal AI/DS Platform Engineer / Architect to lead the architecture and design of enterprise-grade AI/ML platforms for a healthcare client, with an upcoming advanced modeling engagement.

The ideal candidate must have strong hands‑on experience in AWS AI/ML architecture, Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), MLOps, LLMOps, and statistical/predictive modeling.

This role requires 8+ years of experience in designing and architecting production‑level systems, with the ability to independently make architectural decisions and justify technical trade‑offs.

Key Responsibilities

• Lead end‑to‑end architecture and design of enterprise AI/ML platforms using AWS.
• Design and deploy scalable, secure, production‑ready AI/ML infrastructure.
• Architect RAG systems, including embeddings, vector search, hybrid search, and re‑ranking.
• Design LLM gateways, guardrails, evaluation frameworks, and prompt management.
• Build AI/ML solutions using AWS Bedrock, SageMaker, EKS, Lambda, and S3.
• Design and deploy statistical, predictive, and classical machine learning models.
• Develop forecasting and time‑series models, including feature engineering and model validation.
• Establish MLOps and LLMOps practices for model deployment, monitoring, and maintenance.
• Implement Infrastructure as Code using Terraform or AWS CDK.
• Design and maintain CI/CD pipelines.
• Implement monitoring, observability, and performance tracking.
• Ensure cloud security through IAM, VPC, and access controls.
• Optimize infrastructure performance, scalability, and operational costs.
• Evaluate architectural decisions and justify technical trade‑offs.
• Collaborate with engineering and data science teams to translate business requirements into technical solutions.

Required Skills & Experience

• Minimum 8+ years of hands‑on experience in AI/ML engineering, platform architecture, or related engineering roles.
• Proven experience designing production‑grade AI/ML platforms.
• Strong AWS expertise, including Bedrock, SageMaker, EKS, Lambda, S3, IAM, and VPC.
• Experience with OpenSearch or Amazon Kendra.
• Strong understanding of Generative AI, LLMs, RAG, embeddings, hybrid search, and re‑ranking.
• Experience with LLM evaluation, guardrails, prompt management, and model governance.
• Strong Python programming skills.
• Experience in statistical modeling, predictive analytics, classical ML, forecasting, and time‑series analysis.
• Hands‑on experience with Scikit‑learn, XGBoost, and PyTorch.
• Knowledge of MLOps, LLMOps, CI/CD, Terraform/CDK, observability, and FinOps.
• Ability to design complex architectures and explain technical decisions.
• Strong analytical, problem‑solving, and communication skills.
• Availability to work US time‑zone hours.