Senior AI Platform Software Engineer (Java, Spring Boot, LLMs)

Location – Mountain View , CA - Onsite

Exp: 12

Relocation works 

Job Description 

• Design and build the multi-agent execution orchestration and cross-platform execution-caching infrastructure that Pathfinder''s scale and LLM cost efficiency depend on.  

• Drive significant technical initiatives end-to-end, from functional requirements through technical specification, test planning, and production rollout.  

• Act as the technical subject matter expert on agentic execution systems — lead a small team through hard, unprecedented programming and design problems.  

• Prototype and validate proofs of concept quickly; use AI-assisted development tools fluently as part of your own workflow, not just as a subject you build for.  

• Generate technical documentation that communicates architectural and design tradeoffs clearly to both engineering teams and business stakeholders.  

• Operate in Agile/Scrum cadences while retaining the independent judgment to make calls the backlog hasn''t anticipated yet.  

Qualifications 

• Bachelor''s degree in Computer Science, Engineering, or equivalent practical experience; 3 years building cloud-based platforms or services.  

• 8 years developing systems/software for large-scale environments (Java, Springboot), with demonstrated ability to design for scale quickly rather than needing a decade to build the instinct.  

• Hands-on experience building with AI: you''ve shipped something using LLM APIs, agentic frameworks, or AI-assisted coding tools as a core part of the system, not as an add-on. Comfortable reasoning about prompt-driven execution, model behavior under load, and the failure modes that come with non-deterministic systems.  

• Fluent daily user of AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) — this role expects you to build faster because of AI, and to bring that instinct to designing infrastructure where AI agents are the primary actor.  

• Practical experience with microservices and messaging technologies (Micro services, REST, GraphQL, Kubernetes, Kafka, ActiveMQ) and database design across SQL (MySQL) and NoSQL (DynamoDB, Cassandra).  

• Some exposure to the cost/performance mechanics of running LLMs in production — rate limits, token economics, caching strategies, orchestration patterns — is a strong plus even without years of tenure in the space, since almost nobody has years of tenure here yet.  

• Strong CS fundamentals: data structures, algorithms, and system design intuition that holds up with no reference architecture to copy.  
• Working knowledge of TDD and SDLC practices, with the judgment to know when rigor matters and when speed does.