Requirements:
Bachelors degree in CS/EE from a leading university.6+ years of experience with web technologies.
Proven track record as a Senior Full Stack Developer or similar role, with a strong portfolio of successful projects demonstrating technical leadership.
Deep experience with server-side development using Node.js.
Strong understanding and hands-on experience with web technologies, architecture, and design patterns.
Experience using AI-assisted development tools (e.g., Claude Code, Cursor) to enhance productivity, generate and review code, and streamline engineering workflows.
High standards for code quality, testing, and performance, with experience establishing these standards for a team.
Proven experience working on large-scale codebases shared by multiple teams.
Solid understanding of web architecture, RESTful API design, and microservices.
Familiarity with containerization and orchestration tools like Docker and Kubernetes.
Excellent problem-solving skills, with a keen eye for detail and a strong commitment to delivering high-quality work.
Strong communication and interpersonal skills, with the ability to influence and collaborate effectively across teams.
Experience building or integrating LLM-powered features into production applications.
Experience with CI/CD pipelines that incorporate AI-assisted code review or testing.

Requirements:
Your Experience
Backend Engineering: 5+ years of experience building and maintaining production-grade distributed systems.
Languages: Proficiency in Go (Golang) is a strong advantage. We are open to engineers with deep expertise in other backend languages (Java, Python, Rust, C#, or Node.js) who are willing to transition to a Go-primary stack and have a focus on clean, well-tested code.
Fundamentals: Strong grasp of system design, data structures, and algorithms in high-scale cloud environments.
Standards: Experience with CI/CD, comprehensive testing (unit, integration, E2E), and rigorous code reviews.
Cloud: Proficiency in AWS, GCP, or Azure, including cloud-native services.
Reliability: Experience with observability (monitoring, logging, tracing) and system profiling.
Education: B.Sc. or M.Sc. in Computer Science, Software Engineering, or equivalent technical/military experience.
Advantages
Advanced Go: Deep experience with concurrency and memory management patterns.
Distributed SaaS: Background in managing multi-tenant, cloud-based SaaS at scale.
Cybersecurity: Familiarity with threat detection or cloud security infrastructure.
AI Systems: Interest in agentic workflows or prompt engineering in production.

Requirements:
5+ years of development experience as a software engineer.
Deep knowledge of object-oriented programming and other scripting languages: Java, Python, Scala C#, Go, Node.JS and C++.
Strong SQL skills and experience with relational and non-relational databases e.g. (Postgress/Trino/redshift/Mongo).
Experience with developing SAAS products over public cloud infrastructure - AWS/Azure/GCP.
Proven experience designing and developing distributed systems at scale.
Proficiency in queues, locks, scheduling, event-driven architecture, and workload distribution, along with a deep understanding of relational database and non-relational databases.
A demonstrated, genuine AI-first approach to engineering - using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows.
Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.
A deeper understanding of software development best practices and demonstrate leadership skills.
Degree or equivalent relevant experience required. Experience will be evaluated based on the core competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer roles, work experience, etc.)
Desired Skills:
Technical expertise in Generative AI, particularly with RAG systems and Agentic workflows that use large language models.
Experience with Big-Data/ML and S3
Hands-on experience with Streaming technologies like Kafka
Experience with Elastic Search
Experience with Terraform, Kubernetes, Docker
Experience working in a high-paced and rapidly growing multinational organization.

Requirements:
Extensive Backend Expertise: 12+ years of professional experience in backend development, with deep production-level mastery of Golang, Java, Python, or similar languages, and a strong track record of building and operating high-scale distributed services.
Platform Thinking: Proven experience building and evolving platforms - not just features - with a focus on API design (gRPC, REST), service boundaries, multi-tenancy, and shared infrastructure in a high-scale SaaS environment.
Full-Stack Capability: Practical frontend experience with React and TypeScript, with the ability to own production UI components and lead the frontend direction for a backend-heavy product area.
Data & Distributed Systems: Expert-level knowledge of RDBMS (PostgreSQL), query optimization, and extensive experience with high-throughput messaging systems such as Kafka and distributed caches such as Redis.
Cloud-Native Proficiency: Deep experience with AWS/GCP, Kubernetes, Docker, and modern CI/CD patterns in a hyper-scale SaaS environment.
Strategic Communication: Ability to articulate complex technical trade-offs to both technical and non-technical stakeholders, including Product Management, Directors, and VPs.
Cybersecurity Context: (Bonus) Familiarity with security event processing, alerting systems, detection and response workflows, or endpoint and security products in a high-growth cybersecurity context.

Requirements:
What you'll need:

6+ years of backend engineering experience with strong expertise in Node.js and TypeScript.
Hands-on experience building or integrating LLM-powered features or agentic workflows into a production product (not just internal tooling).
Experience with distributed systems and event-driven architectures, and comfort with stores like Kafka, Redis, Elasticsearch, MySQL, and Snowflake.
Strong familiarity with cloud-native environments. AWS experience is a significant advantage.
Deep systems thinking: you design for scale, resilience, and maintainability from the start.
Experience building customer-facing products alongside product managers and designers.
Excellent communication: you can align engineers, product, and non-technical stakeholders around a technical decision.
Proven ability to own and drive complex initiatives with minimal oversight.

Requirements:
Experience: 3+ years of full-stack development experience, preferably in AI/ML domains
AI Development Tools: Hands-on experience with AI-assisted coding environments, IDEs, and agent-based workflows (e.g., Cursor, Windsurf, GitHub Copilot, Codex, Claude Code, and similar platforms)
Model Knowledge: Deep understanding of different AI model capabilities, limitations, and appropriate use cases (GPT-5, Claude, Gemini, etc.)
Frontend Development: Expertise in React, TypeScript and modern web development practices
Backend Development: Strong proficiency in Java with frameworks like Dropwizard
Database & Infrastructure: Knowledge of scalable database design and containerization
Observability Tools: Experience with tracing, monitoring, and evaluation systems
Collaboration: Strong communication skills for working in a distributed, global team environment
Problem Solving: Ability to work in ambiguous environments and solve complex technical challenges
Nice to have:
Open Source: Experience contributing to or maintaining open-source projects
AI/ML Experience: Understanding of Large Language Models, RAG systems, and AI application architectures
Preferred Qualifications:
Experience with model evaluation, prompt engineering, and LLM optimization
Knowledge of distributed systems and high-throughput data processing
Familiarity with ML experiment tracking and model monitoring platforms
Experience with DevOps practices and CI/CD pipelines
Understanding of AI safety, model security, and responsible AI practices

Requirements:
7+ years of backend development experience
Proven experience in the end-to-end development of backend software components, including research, design, development, testing, rollout, and monitoring
Solid understanding of scalability, performance, and reliability tradeoffs
Strong ability to align technical decisions with product and business impact
Ability to quickly learn and adapt to new technologies as needed
Hands-on experience with Docker, Kubernetes, and cloud environments
Advantage: Experience in leadership roles such as Team Lead or Tech Lead

Requirements:
5+ years as a software engineer with strong focus on backend systems and platform development
Deep experience with distributed systems and microservices, including building and maintaining APIs that serve multiple teams
Hands-on expertise with modern infrastructure - AWS, Kafka, RabbitMQ, EKS, SQS, Lambda, Helm, Terraform, or Pulumi
TypeScript proficiency with Rust experience strongly preferred
Platform or core team background - you've built infrastructure that supports multiple development teams, not just end-user features
Developer empathy - you understand what makes engineers productive and can translate that into platform solutions
Ready to work in an office environment most days a week

Requirements:
10+ years of software engineering experience with deep production-level mastery of Go and/or Java (Python a plus), and a strong track record of building and operating high-scale distributed backend services.
A track record of being a recognized subject-matter expert others seek out to review and elevate their designs, with a passion for building high-scale distributed systems.
Platform thinking: proven experience building and evolving platforms, not just features, with a focus on API design (gRPC, REST), service boundaries, multi-tenancy, and shared infrastructure in a high-scale SaaS environment.
Strong background in distributed data processing and microservices, building high-quality, scalable data products that handle millions of events per second.
Deep experience with AWS and/or GCP, Kubernetes, Docker, Postgres, Redis, Kafka, Cassandra, and ClickHouse.
Hands-on experience leveraging AI in the development process (e.g. AI coding assistants and agentic dev tools such as Claude Code, Cursor, or Copilot) and a desire to reshape how a team builds software to better utilize AI.
Experience embedding AI into production services, building agentic and LLM-powered capabilities. Familiarity with modern techniques such as agentic frameworks and orchestration, retrieval-augmented generation (RAG), the Model Context Protocol (MCP), vector databases, prompt engineering, and evaluation and guardrail frameworks for reliable AI systems is a strong advantage.
The ability to turn vaguely specified, complex requirements into efficient, future-proof end-to-end designs, and to drive multi-team initiatives and influence the engineering roadmap.
Strategic communication: able to articulate complex technical trade-offs to both technical and non-technical stakeholders, including Product Management, Directors, and VPs.
Ability to swiftly delve into new products, and to collaborate effectively with local and remote teams across time zones.
Customer focus: you care about delivering value and want to hear directly from customers on how to evolve your systems.
Previous experience developing security-related products is a strong advantage.

Requirements:
7+ years of experience in full stack development (with a strong backend orientation)

Proven experience designing and building scalable, distributed systems in production environments

Deep expertise in Node.js and TypeScript

Strong experience with modern frontend frameworks (React) and advanced JavaScript/TypeScript

Solid understanding of system design, APIs (REST/OpenAPI), and microservices architecture

Experience working with both NoSQL and relational databases. Proficiency with MongoDB and/or PostgreSQL is required, including schema design, query optimization, and handling production-scale data.

Hands-on experience with relational and non-relational databases

Experience working with event-driven architectures (e.g., Kafka, queues, pub/sub systems)

Experience with cloud platforms and serverless architectures (e.g., AWS Lambda)

Experience applying AI-powered development tools (e.g., GitHub Copilot, Cursor) to improve productivity. Familiarity with MCPs and AI agents is a must.

Strong problem-solving skills with the ability to operate independently and take initiative

Excellent communication skills and ability to collaborate across teams

Fluent in English