Senior Software Architect

LinearB is a leading Developer Productivity Insight Platform (DPIP) that empowers engineering teams with actionable insights and workflow automation. Our solutions help improve developer productivity and experience, enable predictable project delivery, and drive profitable engineering. Join us to be part of an innovative company driving efficiency and excellence in software development.

We are looking for a Senior Architect to lead the design and evolution of our system architecture. This is a high-impact role with broad technical ownership, shaping the scalability, reliability, and future direction of our platform.

What You'll Do

• Reporting directly to VP Engineering
• Lead the end-to-end architecture design of our platform and core systems
• Make critical technology decisions and influence long-term technical strategy
• Design and evolve scalable, distributed, and highly available systems
• Ensure performance, reliability, security, and observability across services
• Help implementing SDD in the organization and AI Driven features
• Translate business and product requirements into robust architectural solutions
• Partner closely with R&D, DevOps, Product, and leadership teams
• Drive engineering best practices, standards, and technical excellence
• Mentor engineers and tech leads across teams
  
  

• 10+ years of backend development experience, with at least 3+ years in an architectural or senior technical leadership role
• Strong hands-on experience with Python in production environments
• Proven experience designing and building distributed systems and microservices architectures
• Extensive experience with AWS (S3, SNS, Lambda, Batch, DynamoDB, RDS, etc.)
• Experience with containerization and orchestration technologies (Docker, Kubernetes, Helm, Terraform, ArgoCD)
• Deep understanding of scalability, high availability, resilience, and system design principles
• Experience with monitoring and observability tools such as Datadog
• Proven track record of delivering large-scale, high-quality SaaS products
• Strong understanding of LLM application architecture: prompt/version management, tool/function calling, structured outputs, retrieval-augmented generation (RAG), and agent/workflow patterns
• Proven ability to design for AI reliability and safety: guardrails, policy enforcement, content filtering, hallucination mitigation, and failure-mode design (fallbacks, safe defaults)
• Experience with data governance and privacy for AI: PII handling, retention policies, redaction, tenant isolation, and secure logging/tracing in SaaS environments
• Ability to control cost/performance tradeoffs: model selection strategies, caching, batching, streaming, rate limits/quotas, and capacity planning for AI workloads
• Experience integrating AI services into distributed systems on AWS (e.g., scalable inference/RAG pipelines, async jobs, event-driven orchestration)
  
  

• Deep understanding of networking concepts
• Experience with event-driven architectures
• Experience working with enterprise customers and complex technical environments
• Experience with vector databases / embedding pipelines and retrieval systems (indexing, chunking, relevance tuning)
• Experience with model gateways / multi-provider routing, prompt registries, and feature flagging for model & prompt rollouts
• Familiarity with security & compliance considerations for AI (SOC2-ready controls, audit trails for AI actions, customer data boundaries)
• Experience enabling AI-assisted SDLC / SDD practices (AI in design docs, code review, incident analysis) with governance and standards
  
  

• Put the Customer First
• Take Ownership
• One Team
• Show Product Expertise
• Be Data Driven
• Reach for the Next Level
• Listen Curiously & Speak Courageously