Software Engineer (Staff), Platform Engineering
New
M
micro1AI data infrastructure
Remote; Source API remote eligibility restrictions: United StatesFull-TimeStaff
SalaryBase salary of $250,000 –$300,000. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies.
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Job Details
- Experience
- 10+ years of software engineering experience
- Required Skills
- PythonKubernetesTypeScriptRESTful APIsMicroservicesDistributed Systems
Requirements
- Bring 10+ years of software engineering experience designing, building, and scaling complex production systems.
- Have deep hands-on programming expertise in Python, TypeScript, or similar modern languages.
- Bring extensive experience with distributed systems, microservices, APIs, event-driven architectures, asynchronous processing, and workflow orchestration.
- Demonstrate strong system design and architecture skills, including trade-offs among scalability, reliability, performance, and maintainability.
- Have experience building data-intensive platforms, including data ingestion, processing pipelines, ETL/ELT workflows, and analytics infrastructure.
- Have practical experience with LLMs and agentic systems, including tool calling, agent orchestration, RAG, context management, and evaluation frameworks.
- Have experience with cloud infrastructure such as AWS, GCP, or Azure, containerization, Kubernetes, databases, and CI/CD pipelines.
- Understand engineering quality practices, including automated testing, observability, performance optimization, and production reliability.
- Bring proven technical leadership guiding engineers, driving cross-team initiatives, and owning complex technical projects from design through production.
- Preferred: Experience in AI research labs, AI-native companies, or high-growth technology startups.
- Preferred: Experience with human data infrastructure, foundation model training and evaluation workflows, enterprise AI data platforms, or AI-agent infrastructure.
- Preferred: Familiarity with LangGraph, Temporal, MCP, or similar agentic frameworks and orchestration tools.
Responsibilities
- Lead the design, development, and scalability of platforms for operational workflows, data pipelines, expert lifecycle management, and intelligence delivery.
- Design distributed services, APIs, event-driven architectures, and integrations for complex workflows and high-volume data processing.
- Build systems for expert-generated data, enterprise AI datasets, human feedback, and multimodal AI workflows.
- Architect workflow orchestration for pipeline creation, talent onboarding, subscription management, task execution, and operational processes.
- Develop services that aggregate, process, and surface data, metrics, and insights from multiple systems.
- Design reusable infrastructure for AI agents, including tool calling, orchestration, context management, structured outputs, evaluation, and observability.
- Write production code, lead technical design reviews, troubleshoot complex issues, and establish engineering standards.
- Use AI-assisted development, automated testing, CI/CD, and developer tooling to improve delivery and software quality.
- Mentor engineers, guide architectural decisions, reduce technical debt, and collaborate with Product, AI/ML, Data, and Operations.
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