Founding Cloud Infrastructure Engineer – AI Platform

Valerie Group

. Build Valerie's AI-native platform infrastructure from the ground up .

Posted 9/15/2026full-timeBangalore • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing AWS cloud infrastructure, with a focus on Infrastructure as Code, CI/CD pipelines, and security best practices. Capable of supporting AI-native applications and scalable distributed systems while effectively communicating technical concepts to diverse stakeholders.

Highest-signal resume keywords

AWS Cloud Infrastructure ManagementInfrastructure as Code (Terraform, CloudFormation)CI/CD Pipeline DevelopmentContainerization (Docker, Kubernetes)AI Infrastructure Support

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AWS EC2AWS ECSAWS VPCAWS IAMAWS S3AWS RDSAWS Route 53AWS CloudFrontAWS CloudWatchLoad Balancers

Soft Skills

Strong Communication Skills

Tools & Technologies

TerraformDockerKubernetesAmazon LambdaEventBridgeStep FunctionsRedisKafkaSQSMLOps

Industry Keywords

DevSecOpsDistributed SystemsAI InfrastructureMachine Learning InfrastructureEvent-Driven Architectures

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsDockerEC2KafkaKubernetesLinuxRedisTerraform

About the role

Key responsibilities & impact

Build Valerie's AI-native platform infrastructure from the ground up
Design, build, and scale secure, scalable, and reliable AWS cloud infrastructure
Make architectural and technical decisions for long-term platform growth
Own Infrastructure as Code, CI/CD pipelines, observability, and production reliability
Build infrastructure supporting cloud, DevSecOps, distributed systems, and AI infrastructure
Partner with Product, AI, and Engineering teams to bring new ideas into production
Automate repeatable, secure, and scalable infrastructure
Support AI-native applications and their infrastructure requirements
Participate in the hiring process through role-specific assessments and stakeholder interviews as applicable

Requirements

What you’ll need

Strong hands-on experience building and managing production infrastructure on AWS
Deep knowledge of EC2, ECS, VPC, IAM, S3, RDS, Route 53, CloudFront, CloudWatch, and Load Balancers
Experience with Infrastructure as Code using Terraform or AWS CloudFormation
Strong experience with Docker, containerized environments, and CI/CD pipelines
Solid understanding of Linux, networking, monitoring, debugging, and production incident management
Experience designing secure cloud environments, IAM policies, secrets management, and infrastructure security best practices
Experience building scalable distributed systems and event-driven architectures
Experience supporting AI or machine learning infrastructure, including LLM workloads, vector databases, or retrieval-based systems
Strong communication skills and ability to explain technical trade-offs to technical and non-technical stakeholders
Experience with Kubernetes, Amazon ECS, Lambda, EventBridge, Step Functions, Redis, Kafka, SQS, LangChain, LangGraph, LlamaIndex, Pinecone, Weaviate, Qdrant, pgvector, GPU infrastructure, MLOps, or AI inference systems is a bonus
Experience working in an early-stage startup or building products from zero to one is a bonus

Benefits

Comp & perks

Competitive compensation
Tools needed to do your best work
Opportunities to grow as Valerie grows
Meaningful work with visible impact
High ownership from day one
Collaboration with experienced founders, operators, and specialists
Inclusive workplace
Role-specific assessment or practical exercise where applicable