Senior Software Engineer

First American

. Own the full lifecycle of LLM-powered features from prototyping and prompt design through production deployment, monitoring, and iteration .

Posted 9/16/2026full-timeRemote • California • United StatesSenior💰 $129,300 - $172,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying LLM-powered features, including prompt engineering and evaluation frameworks, while ensuring robust, scalable, and secure integration of AI capabilities. Proven ability to mentor engineers and drive continuous improvement through modern engineering practices and collaboration across cross-functional teams.

Highest-signal resume keywords

LLM-Powered Feature DevelopmentAgentic Systems DesignLarge-Scale Back-End ServicesAI-Assisted Development ToolsCloud-Native Infrastructure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringPrompt EngineeringEvaluation FrameworksDistributed System DesignScalable SolutionsAPI DevelopmentLatency OptimizationCost ManagementRobustness and Quality EngineeringContinuous Delivery

Soft Skills

MentoringCollaborationOutcome-Oriented MindsetInfluencingContinuous Improvement

Tools & Technologies

CursorClaude CodeGitHub CopilotMonitoring ToolsObservability Strategies

Industry Keywords

AI SystemsToken EconomicsMemory ManagementOrchestration LayersFeedback Loops

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

Own the full lifecycle of LLM-powered features from prototyping and prompt design through production deployment, monitoring, and iteration
Build fine-tuning workflows, evaluation harnesses, and inference infrastructure serving users at scale
Design and implement autonomous agent architectures with orchestration layers, memory systems, guardrails, and feedback loops
Define agent behaviors, constraints, and failure modes to ensure safe, explainable, and graceful operation
Design, develop, test, and deploy code for complex functional areas
Architect and implement scalable, highly available, fault-tolerant modern services
Build backend services and APIs enabling secure interaction between AI agents and internal or external systems
Use AI-assisted development tools and help establish team-wide agentic authoring practices
Collaborate with product management, solution architects, AI/ML practitioners, and cross-functional teams
Translate ambiguous business problems into well-scoped, outcome-driven solutions
Implement secure, observable, production-ready solutions
Establish evaluation strategies, cost monitoring, latency budgets, and guardrails
Participate in design, code, artifact, and metrics reviews
Provide regular feedback, mentor peers, and drive continuous improvement
Advocate for modern engineering practices that improve velocity, robustness, and quality

Requirements

What you’ll need

5+ years of experience as a software engineer building production-grade systems
Demonstrated experience taking LLM-powered features from prototype to production, including prompt engineering, evaluation, deployment, and iteration
Hands-on experience building agentic systems, including planning/reasoning loops, tool use, memory/context management, and orchestration
Strong experience building large-scale back-end services and APIs using modern languages and frameworks
Experience using AI-assisted development tools such as Cursor, Claude Code, or GitHub Copilot
Solid understanding of LLM operational concerns, including token economics, latency optimization, model routing, caching strategies, and cost management at scale
Experience designing evaluation frameworks and quality metrics for AI systems
Strong understanding of software engineering principles, cloud-native infrastructure, and distributed system design
Ability to build robust, scalable, reusable solutions that safely integrate AI capabilities into core platforms
Ability to mentor and influence other engineers
Ability to unblock yourself and help accelerate the team in achieving complex, cross-disciplinary goals
Outcome-oriented mindset using metrics and data to evaluate system behavior and development effectiveness
Experience driving engineering best practices through tools and automation
Familiarity with deployment and observability strategies supporting continuous delivery and high availability

Benefits

Comp & perks

Medical insurance
Dental insurance
Vision insurance
401k
PTO/paid sick leave
Employee stock purchase plan
Inclusive workplace culture