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Software Engineer Platform Engineering

Listing for: Confidential
Full Time position Listed on 2026-11-14
Job specializations:
Salary/Wage Range or Industry Benchmark: 250000 - 300000 USD Yearly USD 250000.00 300000.00 YEAR

Job Description & How to Apply Below

Position: Software Engineer (Staff), Platform Engineering

Job Title: Software Engineer (Staff), Platform Engineering

Job Type: Full-time

Location
:
Remote

The Role

We’re looking for a highly technical, hands‑on Staff Software Engineer to lead the architecture, development, and scalability of platforms powering our operations, AI data workflows, and intelligence systems.

You’ll serve as a technical lead across critical engineering initiatives, building the infrastructure that supports complex data pipelines, expert onboarding, workflow orchestration, and the delivery of actionable insights.

This role requires deep engineering expertise, strong architectural judgment, and the ability to drive technical execution across multiple systems. You'll work closely with engineering teams to build reliable, high-performance platforms while incorporating AI agents, intelligent automation, and modern software engineering practices into how we design, build, and operate software.

What You’ll Be Doing

  • Lead Platform Architecture:
    Drive the technical design, development, and scalability of platforms supporting operational workflows, data pipelines, expert lifecycle management, and intelligence delivery.
  • Build Scalable Backend Systems:
    Design distributed services, APIs, event‑driven architectures, and integrations that support complex workflows, high-volume data processing, and cross‑platform communication.
  • Develop AI Data Infrastructure:
    Build systems supporting expert‑generated data, enterprise AI datasets, human feedback, and multimodal data workflows used in AI model training and evaluation.
  • Drive Workflow Orchestration:
    Architect solutions for pipeline creation, talent onboarding, subscription management, task execution, and automated operational processes.
  • Enable Data Intelligence:
    Develop services that aggregate, process, and surface data, metrics, and insights from multiple systems into unified, actionable experiences.
  • Establish Agentic Engineering Foundations:
    Design reusable infrastructure for AI agents, including tool calling, orchestration, context management, structured outputs, evaluation, observability, and reliable execution.
  • Stay Hands‑On:
    Write production‑grade code, lead technical design reviews, troubleshoot complex issues, and establish engineering standards across critical systems.
  • Improve Engineering Productivity:
    Leverage AI‑assisted development, automated testing, CI/CD, and developer tooling to accelerate delivery and improve software quality.
  • Provide Technical Leadership:
    Mentor engineers, guide architectural decisions, reduce technical debt, and collaborate with Product, AI/ML, Data, and Operations to deliver scalable solutions.

What We’re Looking For

  • 10+ years of software engineering experience, with a strong track record of designing, building, and scaling complex production systems.
  • Deep hands‑on programming expertise in Python, Type Script, or similar modern languages, with strong backend engineering fundamentals.
  • Extensive experience with distributed systems, microservices, APIs, event‑driven architectures, asynchronous processing, and workflow orchestration.
  • Strong system design and architecture skills, including the ability to make technical trade‑offs across scalability, reliability, performance, and maintainability.
  • Experience building data‑intensive platforms, including data ingestion, processing pipelines, ETL/ELT workflows, and analytics infrastructure.
  • Practical experience with LLMs and agentic systems, including tool calling, agent orchestration, RAG, context management, and evaluation frameworks.
  • Experience with cloud infrastructure such as AWS, GCP, or Azure, containerization, Kubernetes, databases, and CI/CD pipelines.
  • Strong understanding of engineering quality, including automated testing, observability, performance optimization, and…
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