Software Engineer (Staff), Platform Engineering

Compensation context

Listed annual salary range: $350,000–$600,000/year. The employer’s base salary is stated separately in the Compensation & Benefits Notice below; these figures differ and should not be treated as the same pay guarantee.

Job Title: Software Engineer (Staff), Platform Engineering

Type of job: full-time

Location: Remote

About the role

micro1 wants a deeply technical Staff Software Engineer who still codes, to lead the design, build, and scaling of the platforms behind its intelligence systems, its AI data workflows, and its operations.

As technical lead on key engineering projects, you'll build the infrastructure behind onboarding experts, complicated data pipelines, orchestrating workflows, and delivering insights people can act on.

The job calls for deep engineering skill, sound architecture judgment, and the drive to push technical work forward across many systems. Working closely with engineering teams, you'll build dependable, fast platforms and bring AI agents, smart automation, and current engineering practice into how software is designed, built, and run.

What You’ll Be Doing

• Lead platform architecture: Steer technical design, build-out, and scaling of platforms behind operations workflows, data pipelines, the expert lifecycle, and intelligence delivery.
• Build backend systems that scale: Design distributed services, APIs, event-driven architecture, and integrations for complex workflows, heavy data processing, and communication between platforms.
• Develop AI data infrastructure: Create systems for human feedback, data produced by experts, enterprise AI datasets, and multimodal data used to train and evaluate AI models.
• Drive workflow orchestration: Design solutions for creating pipelines, onboarding talent, managing subscriptions, running tasks, and automating operations.
• Enable data intelligence: Create services that gather, process, and present data, metrics, and insights from many systems in one usable experience.
• Lay foundations for agentic engineering: Design infrastructure AI agents can reuse, covering tool calling, orchestration, context handling, structured outputs, evaluation, observability, and dependable execution.
• Stay hands-on: Ship production-quality code, run technical design reviews, debug hard problems, and set engineering standards for key systems.
• Improve engineering productivity: Use AI-assisted development, automated tests, CI/CD, and dev tools to ship faster and raise software quality.
• Lead technically: Coach engineers, steer architecture choices, pay down technical debt, and work with Operations, Data, AI/ML, and Product on solutions that scale.

What We’re Looking For

• At least 10 years in software engineering and a strong record of designing, building, and growing complicated systems in production.
• Deep coding skill in Python, TypeScript, or comparable modern languages, plus strong backend fundamentals.
• Broad work with microservices, distributed systems, APIs, async processing, event-driven design, and workflow orchestration.
• Strong system design and architecture skill, including weighing trade-offs among scale, reliability, speed, and maintainability.
• Background building data-heavy platforms, covering ingestion, processing pipelines, ETL/ELT, and analytics infrastructure.
• Real-world work with LLMs and agent systems: tool calling, agent orchestration, RAG, context handling, and evaluation frameworks.
• Background with containers, Kubernetes, databases, CI/CD pipelines, and cloud infrastructure on AWS, Azure, or GCP.
• Solid grasp of engineering quality: automated testing, observability, performance tuning, and reliability in production.
• Clear technical leadership: guiding engineers, pushing initiatives across teams, and owning complicated projects from design to production.
• Strong ownership and drive to deliver, able to handle uncertainty, crack hard technical problems, and ship in fast-moving settings.

Preferred Qualifications

• Background at AI research labs, AI-native firms, or fast-growing tech startups.
• Work on human data infrastructure: datasets created by experts, labeling, preference data, workflows with a human in the loop, and pipelines for evaluating models.
• Knowledge of how foundation models are trained and evaluated, including human demonstrations, robotics data, and multimodal datasets.
• Background creating retrieval systems, AI data platforms for enterprises, or infrastructure that AI agents run on.
• Practical work with agent frameworks and orchestration tools like LangGraph, Temporal, MCP, or comparable technology.
• Background designing analytics that run in real time, operational intelligence, and systems that pull data together from many platforms.
• Knowledge of AI-assisted dev tools, agent-led engineering workflows, and current developer productivity practice.

Compensation & Benefits Notice

Nationally, base pay for this full-time job runs $250,000–$300,000. Every employee can receive equity, and bonuses tied to performance may also apply depending on the role and company policy. Benefits cover health-insurance premiums (reimbursed at up to 100%), paid time off, a 401(k) with a company match, and other perks meant for a remote-first team that performs at a high level.

micro1 hires on an equal-opportunity basis. Every qualified applicant is considered without regard to age, color, disability, national origin, race, religion, sex (pregnancy, gender identity, and sexual orientation included), veteran status, genetic information, or any other trait that applicable local laws, ordinances, or regulations protect. Applicants who need help or a reasonable accommodation while applying can ask for it.

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Application process

Submit your application through NorthStar. Employer screening may follow after submission.