Principal Engineer – AI Platform, Forward Deployed Engineering, AI Builder Experience

Target

. Provide technical leadership for how engineering teams build, integrate, deploy, and operate AI-powered applications .

Posted 10/5/2026full-timeUnited StatesLead💰 $168,000 - $356,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and delivering production-grade AI solutions, including LLM-powered applications, while providing technical leadership across engineering teams. Proficient in building developer-facing capabilities and ensuring scalable integration and deployment of AI systems.

Highest-signal resume keywords

AI Application DevelopmentProduction-Grade System ArchitectureDeveloper Tooling and APIsDistributed System DesignTechnical Leadership and Mentorship

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringAI/ML SystemsModel IntegrationCloud PlatformsCI/CDObservability ToolingPerformance OptimizationSecurityAgile PrinciplesTechnical Documentation

Soft Skills

Excellent CommunicationInfluencing SkillsOwnershipTechnical JudgmentContinuous Learning

Tools & Technologies

Agent Development FrameworksFrameworksLibrariesContainersOrchestrationDeveloper ToolingReference ArchitecturesSelf-Service PlatformsEvaluation ToolingMonitoring Tools

Certifications & Qualifications

MS or PhD in Computer ScienceEngineeringMathematicsStatistics

Industry Keywords

AI-Powered ApplicationsLarge-Scale Software PlatformsScalabilityReliabilityProduction Deployment

Tech Stack

Tools & technologies

CloudDistributed Systems

About the role

Key responsibilities & impact

Provide technical leadership for how engineering teams build, integrate, deploy, and operate AI-powered applications
Architect and deliver production-grade AI solutions, including agentic and LLM-powered applications
Establish scalable patterns for model and agent integration, enterprise context, evaluation, observability, deployment, and production operations
Bring platform expertise directly to engineering teams and help move AI solutions from experimentation into production
Identify recurring challenges across forward deployed engagements and turn learnings into reusable APIs, SDKs, frameworks, developer tooling, reference architectures, and self-service platform capabilities
Provide technical leadership for the end-to-end AI developer experience, including onboarding, development, experimentation, testing, evaluation, debugging, deployment, and observability
Partner with platform engineering, product, architecture, and application teams to influence platform roadmaps and establish engineering standards
Create reference implementations that enable responsible AI adoption at scale
Evaluate and recommend emerging AI frameworks and tooling
Publish learnings and reusable patterns
Mentor senior engineers and influence technical direction across the AI engineering ecosystem
Follow Agile principles, participate in code reviews, and create maintainable, well-tested codebases with relevant documentation

Requirements

What you’ll need

MS or PhD in Computer Science, Engineering, Mathematics, Statistics, another quantitative discipline, or equivalent industry experience
8+ years of experience designing, building, and operating large-scale software platforms, developer platforms, AI/ML systems, or distributed systems in production environments
Strong hands-on software engineering experience
Ability to architect and deliver production-grade systems
Experience designing and delivering AI applications, including LLM-powered or agentic systems
Understanding of model integration, context and retrieval patterns, tool integration, evaluation, and production operations
Experience building developer-facing capabilities such as APIs, SDKs, frameworks, libraries, developer tooling, templates, or self-service platform experiences
Experience with model APIs, agent development frameworks, evaluation and observability tooling, cloud platforms, containers, orchestration, CI/CD, and operational monitoring
Strong understanding of distributed system design, platform architecture, scalability, reliability, performance optimization, security, and production deployment
Ability to partner with engineering and product teams and translate implementation challenges into scalable technical solutions
Ability to operate across architecture, prototyping, implementation, production deployment, and operational maturity
Ability to translate ambiguous problems into technical approaches and create technical documentation, reference architectures, narratives, and recommendations
Excellent communication and influencing skills
Ability to mentor senior engineers and influence architecture and engineering standards without direct authority
Strong ownership, technical judgment, and ability to balance near-term delivery with long-term platform scalability
Experience working across functions, organizations, and geographies
Commitment to continuous learning and knowledge sharing

Benefits

Comp & perks

Comprehensive health benefits, which may include medical, vision, dental, and life insurance
401(k)
Employee discount
Short-term disability
Long-term disability
Paid sick leave
Paid national holidays
Paid vacation
Financial, education, and well-being benefits and programs
Remote work arrangement options
Hybrid/Flex for Your Day work arrangement options
Remote team members may travel to HQ up to 4 times a year