Backend Engineer - AI Developer Platform Job at N26 (Berlin)

GCP AI Platform Architect / Lead AI Platform Engineer

Our client is an innovative technology company specializing in the development o...

Location

Poland , Kraków

Salary:

Not provided

TeamQuest Sp. z o. o.

Expiration Date

Until further notice

Requirements

GCP Expertise (verifiable - ask for production examples): GCP is their primary cloud not secondary experience alongside AWS/Azure. Production deployments across most of: Vertex AI, Cloud Run or GKE, Pub/Sub, BigQuery, Secret Manager, VPC Service Controls, IAM + Workload Identity. Has designed for GCP from scratch, not migrated from another cloud, end-to-end ownership
AI / Backend Engineering: Python is the primary language - production-grade service/API development, not scripting or data science only. Strong track record building distributed systems and integrating LLMs.
Agentic Architecture (must be production, not PoC): Hands-on production experience with at least one: LangGraph, Google ADK, CrewAI, or custom multi-agent orchestration layer. RAG pipelines shipped to production. Google ADK: candidate must be able to explain what it is, when to use it, and how it compares to LangGraph and custom orchestration. AI agent workflows, ReAct prompting, and Function Calling in production environments
Multi-Tenant Architecture: Has designed a multi-tenant SaaS platform end-to-end - not just contributed. Can articulate tenant isolation strategies: IAM boundary design, data isolation per tenant, VPC controls.
API Design & Integrations: Proven ability to create secure, high-performance APIs capable of asynchronously managing traffic and communication between multiple decoupled services.
Enterprise Security: Practical knowledge of data isolation in multi-tenant SaaS architectures, IAM, and securing cloud-based environments.
Vector Databases: Hands-on experience with semantic search and at least one of: Pinecone, Weaviate, pgvector, or Vertex Matching Engine.

Job Responsibility

System Architecture: Design and develop a scalable, cloud-native architecture on Google Cloud Platform (GCP) that meets enterprise security and multi-tenant data isolation requirements for a SaaS environment
AI Agent Orchestration: Architect and implement autonomous, multi-step AI workflows with a clear separation of agent responsibilities (retrieval, analysis, reasoning, response generation)
Hands-on Core Development: Actively contribute to core system development-coding orchestration logic, designing services, optimizing performance, and building secure API integrations for routing queries across internal and external agents
Frontend Enablement: Design the backend layer, streaming protocols, and APIs to seamlessly support and integrate with advanced conversational UIs
Data Management & Extensibility: Build a robust backend capable of processing qualitative and social data, ensuring the platform is easily extensible to incorporate new data sources

What we offer

Attractive salary
Full remote work
Social benefits:sporto card,healthcare insurance

Fulltime

GCP AI Platform Architect / Lead AI Platform Engineer

Our client is an innovative technology company specializing in the development o...

Location

Poland , Katowice

Salary:

Not provided

TeamQuest Sp. z o. o.

Expiration Date

Until further notice

Requirements

GCP Expertise (verifiable - ask for production examples): production deployments across most of: Vertex AI, Cloud Run or GKE, Pub/Sub, BigQuery, Secret Manager, VPC Service Controls, IAM + Workload Identity
Has designed for GCP from scratch, not migrated from another cloud, end-to-end ownership
AI / Backend Engineering: Python is the primary language - production-grade service/API development, not scripting or data science only
Strong track record building distributed systems and integrating LLMs
Agentic Architecture (must be production, not PoC): Hands-on production experience with at least one: LangGraph, Google ADK, CrewAI, or custom multi-agent orchestration layer
RAG pipelines shipped to production
Google ADK: candidate must be able to explain what it is, when to use it, and how it compares to LangGraph and custom orchestration
AI agent workflows, ReAct prompting, and Function Calling in production environments
Multi-Tenant Architecture: Has designed a multi-tenant SaaS platform end-to-end - not just contributed
Can articulate tenant isolation strategies: IAM boundary design, data isolation per tenant, VPC controls

Job Responsibility

System Architecture: Design and develop a scalable, cloud-native architecture on Google Cloud Platform (GCP) that meets enterprise security and multi-tenant data isolation requirements for a SaaS environment
AI Agent Orchestration: Architect and implement autonomous, multi-step AI workflows with a clear separation of agent responsibilities (retrieval, analysis, reasoning, response generation)
Hands-on Core Development: Actively contribute to core system development-coding orchestration logic, designing services, optimizing performance, and building secure API integrations for routing queries across internal and external agents
Frontend Enablement: Design the backend layer, streaming protocols, and APIs to seamlessly support and integrate with advanced conversational UIs
Data Management & Extensibility: Build a robust backend capable of processing qualitative and social data, ensuring the platform is easily extensible to incorporate new data sources

What we offer

Attractive salary
Full remote work
Social benefits: sport card, healthcare insurance

Fulltime

Backend Engineer (AI Platform)

Plaud is building the world's most trusted AI work companion for professionals t...

Location

Singapore , Singapore

Salary:

Not provided

Plaud

Expiration Date

Until further notice

Requirements

Minimum 3 years of backend or AI engineering experience
At least 1+ years specifically in LLM application architecture
Deep practical knowledge of advanced agent patterns (e.g., Plan-Act-Reflection)
Proven ability to design complex distributed systems
Experience defining API standards and data protocols for cross-team usage

Job Responsibility

Agent Architecture Design: Designed the AI Agent architecture and implemented the "Plan-Act-Reflection" agentic flow
Skill Design: Developed agent skills including Function Calling, MCP Server integration, and Streaming APIs
Design DAG (Directed Acyclic Graph) reasoning flows to break down ambiguous user requests into executable steps
Solve critical runtime challenges like "Context Rot" (context overflow) by designing strategies for context offloading, isolation, and intelligent compression
RFT: Architect the Automated Data Flywheel system. Design Reward Functions and LLM-as-a-judge pipelines to programmatically evaluate agent performance and drive reinforcement learning

What we offer

Market-competitive compensation
Global exposure
Vibrant, creativity-fueled work atmosphere

Fulltime

AI Platform Engineer, Backend

As an AI Platform Backend Engineer, you will own and build the core backend syst...

Location

United States , San Francisco Bay Area

Salary:

Not provided

Brain Co.

Expiration Date

Until further notice

Requirements

5+ years of experience building backend systems or platforms in production
Strong fundamentals in distributed systems (consistency, availability, failure modes, retries, idempotency)
Deep proficiency in at least one backend language (Go, Typescript, Rust, Python, or similar)
Experience designing, operating, and evolving APIs and services at scale
Proven ability to design systems from first principles
Experience building shared infrastructure, internal platforms, or developer-facing services
Strong intuition for developer experience and long-term maintainability
Experience owning services with real uptime and operational responsibility
Familiarity with observability tooling (metrics, logging, tracing) and incident response

Job Responsibility

Design, build, and operate foundational backend services and data pipelines that power Brain Co.’s AI platform
Take end-to-end ownership: architecture, implementation, deployment, and long-term maintenance
Build systems with strong guarantees around correctness, fault tolerance, and observability
Design for real uptime expectations in enterprise and government environments
Design modular, reusable backend architectures and APIs (REST, gRPC, event-driven)
Make sound architectural tradeoffs with a long-term platform mindset
Break down open-ended, complex problems into clear technical designs
Move from first principles to production-ready systems with speed and rigor
Improve latency, throughput, and cost efficiency through profiling, thoughtful system design, and iteration
Work closely with Product, ML, Infrastructure, and customer-facing teams

What we offer

Competitive salary plus equity
Medical, Dental, and Vision coverage
401(k)
Unlimited PTO
Daily lunches
Commuter benefits

Fulltime

Senior ML Platform Engineer, AI Platform

We are seeking a skilled and passionate ML Platform Engineer to join our team an...

Location

Singapore , Singapore

Salary:

Not provided

Airwallex

Expiration Date

Until further notice

Requirements

5+ years in backend software development
at least 2+ years focus on AI/ML Platform or MLOps infrastructure
deep expertise in MLOps practices, including automated deployment pipelines, model optimization, and production lifecycle management
proven experience designing and implementing low-latency model serving solutions
proficiency in Python
skill in writing high-quality, maintainable code
experience in design and development of large-scale distributed, high concurrency, low-latency inference, high availability systems
excellent communication and mentoring abilities
a relevant degree in Computer Science, Mathematics or related fields

Job Responsibility

Platform Development: Design, build, and maintain the end-to-end MLOps platform using Kubernetes and Cloud Services
Infrastructure as Code (IaC): Use Terraform or similar tools to manage, provision, and scale all ML-related infrastructure securely and efficiently
Pipeline Automation: Implement and optimize CI/CD/CT (Continuous Integration, Delivery, Training) pipelines to automate model training, testing, packaging, and deployment using tools like Argo and Kubeflow Pipelines
Serving Infrastructure: Build highly available, low-latency, and high-throughput model serving infrastructure
Observability: Implement robust monitoring, alerting, and logging solutions to track infrastructure health, model performance, and data/model drift
Tooling & Support: Evaluate, integrate, and support ML tools such as Feature Stores and distributed model training pipelines
Security & Compliance: Ensure platform security, implement RBAC (Role-Based Access Control), and manage secrets for sensitive data and production environments
Collaboration: Work closely with Data Scientists and ML Engineers to understand their needs and provide technical guidance on best practices for scaling their models

Fulltime

Senior Machine Learning Engineer, AI Platform

The AI Platform team is responsible for building the foundational infrastructure...

Location

United States; Canada

Salary:

139000.00 - 218000.00 USD / Year

Mozilla

Expiration Date

Until further notice

Requirements

Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent
Strong experience developing in Python for machine learning systems, backend services, or distributed data processing
Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure
Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies)
Hands-on experience working with GPU-based workloads and accelerated computing in production settings
Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment
Ability to independently scope and drive technical initiatives while balancing product and operational priorities
Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems
Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams

Job Responsibility

Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments
Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence
Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads
Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization
Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation
Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines
Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features
Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing
Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews

What we offer

Generous performance-based bonus plans
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting
Quarterly all-company wellness days
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

Senior Azure AI Platform Engineer

We’re partnering with a rapidly growing, private equity–backed technology compan...

Location

United States , Park Ridge

Salary:

130000.00 USD / Year

Strategic Employment Partners

Expiration Date

Until further notice

Requirements

6+ years of software engineering experience
Strong hands-on experience with C# and .NET
Experience building or integrating AI/ML solutions in production environments
Cloud experience (Azure preferred
AWS/GCP acceptable)
Strong experience with REST APIs and modern backend architecture
Comfortable working in a hybrid environment (3 days onsite weekly)

Job Responsibility

Build and integrate AI-powered capabilities into a .NET application stack
Develop backend services and APIs using C#/.NET
Design and implement cloud-native components and microservices in Azure
Integrate Azure AI / OpenAI (or similar cloud AI services) into real-world workflows
Partner with product and business teams to translate AI ideas into production-ready solutions
Help establish patterns and best practices for scalable, secure AI adoption

Fulltime

Senior Staff Full Stack Engineer– AI Platform

We are looking for senior software engineers who will have front end responsibil...

Location

India , Karnataka

Salary:

Not provided

Teradata

Expiration Date

Until further notice

Requirements

12+ years of software engineering experience building large-scale applications
Strong expertise in modern frontend development with React and JavaScript/TypeScript
Experience building full-stack applications with scalable backend services
Backend experience with Node.js, Java, or Python
Demonstrated experience designing distributed systems and APIs
Experience working in fast-paced product development environments
Strong ability to lead technical initiatives across multiple teams
Strong knowledge in writing Automated Test Suites using frameworks like Jasmine, Protractor, Mocha, Cypress, Jest, or Selenium
Good working knowledge on Java/Python and experience with development
Familiarity with TDD and concepts like mocking and stubbing for unit / integration tests

Job Responsibility

Lead architecture and development of scalable full-stack systems, delivering high-quality customer-facing applications using React and modern JavaScript/TypeScript frameworks
Design and build distributed backend services and APIs using Node.js, Java, or Python to support frontend applications and AI-powered capabilities
Drive adoption of AI-assisted development workflows, including translating AI-generated prototypes into production-grade software and improving developer productivity through modern tooling
Design and implement AI-powered features and agent-based systems, integrating LLM-driven capabilities into product experiences
Lead system design for large-scale applications, ensuring performance, reliability, and maintainability across services and platforms
Provide technical leadership across teams, mentoring engineers, guiding architectural decisions, and establishing best practices
Partner with product, design, and cross-functional teams to rapidly prototype, iterate, and ship impactful features in a fast-paced environment
Evaluate and integrate emerging technologies, particularly in AI, developer tooling, and platform capabilities

What we offer

people-first culture
flexible work model
focus on well-being
inclusive environment

Fulltime

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Backend Engineer - AI Developer Platform

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