AI Software Engineer – Staff/Principal

Seeq Corporation

. Define architecture, patterns, and technical approaches for scalable backend systems supporting AI and agentic applications .

Posted 9/22/2026full-timeRemote • United StatesLead💰 $170,000 - $205,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in backend engineering and AI systems, with a strong focus on building scalable, reliable, and maintainable architectures for agentic applications. Proven ability to lead complex projects, mentor teams, and integrate emerging AI technologies into production environments.

Highest-signal resume keywords

Python ProgrammingBackend EngineeringAI Systems DevelopmentTechnical LeadershipKubernetes Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend ServicesAPIs DevelopmentLarge-Scale Distributed SystemsData-Intensive WorkflowsAgentic SystemsOrchestration PatternsEvaluation StrategiesObservabilitySQLRelational Databases

Soft Skills

Strong CommunicationMentoringCoaching

Tools & Technologies

AI/LLM FrameworksSDKsContainerized Runtime EnvironmentsSaaS Environments

Industry Keywords

Generative AIAgentic SystemsPlatform EngineeringProduction AI ConcernsIntegration with Enterprise Platforms

Tech Stack

Tools & technologies

Distributed SystemsKubernetesPostgresPythonSQL

About the role

Key responsibilities & impact

Define architecture, patterns, and technical approaches for scalable backend systems supporting AI and agentic applications
Own complex, ambiguous projects from concept through production, coordinating across engineers, teams, and stakeholders
Design and build agentic systems supporting agent routing, orchestration, tool use, evaluations, runtime infrastructure, sandboxing, and agent-to-agent communication
Define backend services, runtime environments, interfaces, and architectural patterns for AI-enabled applications
Develop reliable backend services and APIs supporting AI workloads across large data volumes and complex workflows
Build shared AI platform services, APIs, libraries, orchestration patterns, runtime infrastructure, and developer-facing capabilities
Establish approaches for evaluating agentic output, monitoring system behavior, and improving reliability, safety, and observability
Build integrations between AI agents, internal services, and third-party enterprise platforms
Evaluate emerging AI technologies and translate them into maintainable production systems
Work directly with customers during early deployments and incorporate real-world learnings into the product
Provide technical mentorship in backend architecture, platform engineering, agentic systems, AI engineering, and operational excellence
Surface risks, challenge assumptions, and identify improved technical approaches
Collaborate with product managers and owners to develop and hone a vision for generative AI in analytics engineering

Requirements

What you’ll need

Minimum 10+ years of professional software engineering experience, including experience operating at Staff or equivalent scope
A substantial portion of recent experience focused on generative AI or agentic systems
Proven track record leading complex AI, agentic, or platform initiatives from concept through production
Extensive hands-on experience building and operating agentic systems, including agents, routing/orchestration, tool use, evaluations, runtimes, sandboxing, or related infrastructure
Deep expertise in Python and backend engineering, including large-scale distributed systems, services, APIs, and data-intensive workflows
Experience designing or owning shared platform services or infrastructure used by multiple engineering teams
Experience with modern AI/LLM frameworks, SDKs, or orchestration tooling used to build production AI and agentic applications
Experience developing evaluation strategies and observability for AI or agentic systems
Familiarity with SQL and relational databases such as PostgreSQL
Experience deploying and operating production systems in Kubernetes or another containerized runtime environment
Experience building and operating software in a SaaS environment
Strong understanding of production AI concerns including reliability, monitoring, performance, cost, and failure handling
Ability to evaluate emerging AI approaches and translate them into pragmatic, maintainable software
Demonstrated ability to take ownership of ambiguous technical problems and independently drive them forward
Proven technical leadership of engineers and teams while maintaining strong individual hands-on contribution
Strong communication skills and experience mentoring and coaching engineers
Preferred: experience architecting multi-agent or complex agentic platforms used across multiple teams or products
Preferred: experience defining shared AI or backend platform capabilities used broadly across an engineering organization
Preferred: experience with retrieval architectures such as vector search, hybrid retrieval, re-ranking, or RAG
Preferred: experience integrating AI agents with third-party enterprise platforms
Preferred: experience working with industrial, operational, or time-series data
Preferred: experience building software products used by technical or engineering-focused customers
Preferred: background in mechanical, chemical, process, or another engineering discipline before moving into software

Benefits

Comp & perks

Competitive salary, equity, and cash bonus incentives
Unlimited PTO
Internet and mobile phone reimbursements
Annual company meetups
4-week paid sabbatical every 7 years at Seeq
Vacation bonus program
Generous home office allowance
Pet-friendly workspace
A job you'll love!