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Airbyte

Staff Backend Engineer – Agent Infrastructure

Airbyte

. Build Airbyte MCP infrastructure enabling AI agents to configure Airbyte, troubleshoot syncs, and access connected data .

Posted 11/11/2026full-timeSan Francisco • California • United StatesLead💰 $250,000 - $280,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates extensive experience in backend engineering, system design, and building AI-powered products, with a strong focus on reliability, observability, and operational excellence. Proven ability to lead technical direction and influence architectural decisions while effectively communicating priorities and tradeoffs.

Highest-signal resume keywords
Backend EngineeringDistributed Systems DesignAI-Powered Product DevelopmentSystem Design and ReliabilityTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Software EngineeringAPI DevelopmentAsynchronous WorkflowsConcurrency ManagementPrototypingDebuggingObservabilityFailure HandlingSemantic ModelsData Infrastructure
Soft Skills
Exceptional Written CommunicationOwnershipProduct Instincts
Tools & Technologies
AirbyteLLMsKafkaPostgresSparkMCPVector SearchWorkflow EnginesDeveloper PlatformsSaaS APIs
Industry Keywords
AI AgentsSemantic SearchEnterprise DataTechnical ExperimentsCross-Team Collaboration

Tech Stack

Tools & technologies
Distributed SystemsKafkaPostgresSpark

About the role

Key responsibilities & impact
  • Build Airbyte MCP infrastructure enabling AI agents to configure Airbyte, troubleshoot syncs, and access connected data
  • Design reliable, secure, and observable interfaces across the connector ecosystem
  • Build and operate semantic search and retrieval infrastructure over enterprise data
  • Develop and maintain semantic models for consistent, verifiable business definitions
  • Build realistic, stateful SaaS replicas for agent development and testing
  • Turn product hypotheses into focused technical experiments and prototypes
  • Work with customers, Product, Design, and customer-facing teams to understand problems and incorporate feedback
  • Evaluate technical approaches and influence product direction
  • Design and implement backend systems, APIs, and infrastructure for AI, data, and developer products
  • Build reliable, observable systems with failure handling, debugging, and operational safeguards
  • Move promising prototypes into production and improve them based on usage, incidents, and customer feedback
  • Own architecture and execution across technical design, implementation, rollout, and iteration
  • Lead cross-team technical decisions, align interfaces and dependencies, and influence broader architecture
  • Communicate priorities, risks, and tradeoffs and follow through on commitments

Requirements

What you’ll need
  • 10+ years of software engineering experience building and operating production systems
  • Strong backend engineering fundamentals and experience designing distributed systems
  • Experience building complex systems involving APIs, asynchronous workflows, concurrency, queues, state, retries, or distributed execution
  • Hands-on experience building and shipping AI-powered products using LLMs, agents, RAG, tool calling, MCP, or similar technologies
  • Experience with orchestration systems, workflow engines, developer platforms, or infrastructure products
  • Strong system design skills and ability to reason about reliability, scale, observability, and failure modes
  • Demonstrated ability to lead technical direction across teams and influence architectural and engineering decisions
  • Ability to move quickly from prototype to production without sacrificing engineering quality
  • Strong product instincts and comfort operating in ambiguous, 0-to-1 environments
  • Exceptional written communication skills
  • Strong bias toward ownership and shipping
  • Experience building and operating AI agents in production, including debugging, observability, and evaluation (nice to have)
  • Experience building agent infrastructure, agent platforms, or evaluation systems (nice to have)
  • Experience with retrieval systems, vector search, search infrastructure, or semantic models (nice to have)
  • Experience building developer tools, platform infrastructure, or integrations with third-party SaaS APIs (nice to have)
  • Experience with data infrastructure such as Kafka, Iceberg, Postgres, Spark, or modern data warehouses (nice to have)
  • Willingness to work in the San Francisco office 4 days/week

Benefits

Comp & perks
  • Flexible PTO with a culture that encourages at least 25 days off annually
  • 16 weeks fully paid parental leave for all parents
  • Comprehensive medical, dental, and vision coverage for employees and dependents
  • 401(k) retirement plan
  • Professional development budget, conference sponsorship, and book reimbursement
  • Commuter benefits and monthly internet reimbursement
  • Breakfast and lunch in the San Francisco office
  • Collaborative, in-person culture focused on learning, growth, and impact
  • Equity