Software Engineer – Infrastructure

Reindeer

Backend Engineer specializing in infrastructure for AI-driven complex workflows at an early-stage startup. Focus on building and scaling infrastructure that powers autonomous AI agents.

Posted 7/1/2026full-timeTel Aviv • 🇮🇱 IsraelMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying scalable infrastructure on cloud platforms, with a strong focus on data pipelines, containerization, and compliance with data privacy standards. Proven ability to collaborate with cross-functional teams to support AI-driven applications and ensure production-grade reliability.

Highest-signal resume keywords

Infrastructure EngineeringCloud Deployment (AWS, GCP, Azure)Containerization and Orchestration (Docker, Kubernetes)Data Pipeline ManagementCI/CD Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQL (PostgreSQL, MySQL)NoSQL (Document DB, Vector DB)OAuth2JWTRPA ToolsGraph Databases (Neo4j)GoRustAI/ML Frameworks (TensorFlow, PyTorch, Hugging Face)

Tools & Technologies

DockerKubernetesAWSGCPAzure

Industry Keywords

Data Privacy Standards (GDPR, HIPAA)Document ProcessingHigh-Throughput WorkloadsAPIsObservability and Monitoring

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsDockerERPGoGoogle Cloud PlatformKubernetesMySQLNeo4jNoSQLPostgresPythonPyTorchRPARustSQLTensorflow

About the role

Key responsibilities & impact

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.
Build and scale the backend systems that support high-throughput document processing and data extraction workloads.
Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.
Own containerization and orchestration (Docker, Kubernetes) for all production workloads.
Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.
Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.
Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).
Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.
Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.
Build observability and monitoring systems to track infrastructure health, performance, and cost.
Collaborate with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.
Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

Requirements

What you’ll need

5+ years of experience in backend or infrastructure engineering
Proven track record of building and scaling infrastructure in production environments.
Proficiency in Python.
Databases: Proficiency in SQL (PostgreSQL, MySQL) and NoSQL (e.g. Document DB, Vector DB).
Deep experience deploying and scaling large production applications on AWS, GCP, or Azure.
Containerization and orchestration: Docker, Kubernetes.
Strong understanding of OAuth2, JWT, and best practices for securing distributed systems.
Experience with RPA (Robotic Process Automation) tools (bonus skill).
Familiarity with graph databases (Neo4j) for managing complex workflows (bonus skill).
Familiarity with Go and Rust (bonus skill).
Experience working alongside AI/ML teams using frameworks like TensorFlow, PyTorch, or Hugging Face (bonus skill).

Benefits

Comp & perks

Health insurance
Flexible work arrangements
Professional development opportunities