Technical Lead

About Muvr

Muvr is building the future of on-demand logistics and moving services. Our platform powers real-time booking, pricing, matching, payments, and fulfillment across customers, drivers, and partners. We operate in the physical world, so reliability, correctness, and operational readiness are core engineering requirements. As we scale, we need technical leaders who can deliver high-impact capabilities while protecting platform integrity, performance, and long-term maintainability.

Role Overview

The Technical Lead is a hands-on senior engineer responsible for driving technical execution across a core area of the platform. You will lead architecture and implementation for key initiatives, raise the engineering bar through strong design and delivery standards, and ensure what we build works reliably in production and in real-world workflows.

This is not a people-manager role. You will lead through technical judgment, architecture decisions, code reviews, mentorship, and high-quality execution. You will work closely with Product, Design, and Operations to scope correctly, ship safely, and improve reliability over time.

Key Responsibilities

1) Technical Leadership and Architecture

• Lead technical design for key features, including API contracts, data flows, domain boundaries, and failure-mode handling.
• Ensure solutions are scalable, reliable, and maintainable, with clear service ownership and interface definitions.
• Make pragmatic architecture decisions that increase long-term leverage without overengineering.
• Document key technical decisions, system behavior, and service expectations so teams can build and operate with confidence.
  

2) Delivery and Engineering Excellence

• Drive end-to-end execution, including design reviews, implementation, testing strategy, release readiness, and post-launch stabilization.
• Set and reinforce engineering best practices across coding standards, review quality, test discipline, performance profiling, and technical documentation.
• Ensure production readiness through structured logs, metrics, tracing, alerting, and monitoring tied to customer and operational outcomes.
• Improve deployment safety through feature flags, staged rollouts, backward compatibility, and rollback plans.
  

3) Mentorship and Team Enablement

• Mentor engineers through code reviews, pairing, architecture discussions, and technical coaching.
• Raise the quality bar by sharing patterns, preventing repeated mistakes, and improving day-to-day engineering workflows.
• Provide technical leadership during planning by clarifying scope, identifying risks early, and proposing safe delivery paths.
• Support onboarding by improving documentation, runbooks, and architecture clarity within your domain.
  

4) Production Ownership

• Troubleshoot production issues and lead technical incident response for your domain or service area.
• Perform root-cause analysis and drive corrective actions that reduce repeat incidents.
• Reduce operational toil by simplifying workflows, improving tooling, and automating repetitive tasks.
• Improve observability so issues are detected earlier, diagnosed faster, and resolved more effectively.
  

5) Cross-Functional Collaboration

• Work with Product and Design to translate business requirements into robust technical solutions.
• Push for clarity when requirements are ambiguous, and communicate tradeoffs across quality, speed, risk, complexity, and performance.
• Partner with Operations to ensure solutions match real-world execution needs and operational constraints.
• Contribute to stronger cross-functional execution through early risk communication and disciplined technical scoping.
  

6) AI-Enabled Productivity and Execution

• Use AI tools thoughtfully to improve productivity, engineering research, documentation quality, debugging efficiency, and execution speed.
• Apply AI responsibly to support design exploration, code review preparation, troubleshooting, and workflow improvement while maintaining correctness, security, and sound engineering judgment.
• Identify where AI agents, agentic workflows, or engineering automations can improve recurring work such as code investigation, test generation, incident triage, PR review prep, runbook drafting, log analysis, documentation, and internal developer workflows.
• Help establish practical guardrails for using AI in engineering so quality, security, maintainability, and production safety are not compromised.

Qualifications

Required

• 5+ years of software engineering experience building and operating production systems.
• Strong system design skills across services, APIs, data modeling, and distributed systems fundamentals.
• Proven track record of leading technical projects end-to-end and influencing decisions across engineering teams.
• Strong communication skills, with the ability to explain tradeoffs, risks, and design decisions clearly to both technical and non-technical stakeholders.
• Comfortable owning production outcomes, including stability, performance, debuggability, and operational readiness.
• Comfortable using AI tools to improve efficiency and work quality, with a willingness to learn emerging AI workflows and apply them responsibly.
• Experience using AI agents, agentic workflows, or automation systems to support recurring engineering work such as code analysis, test generation, documentation drafting, PR review support, incident investigation, log analysis, workflow automation, or internal tooling.

Preferred

• Experience with marketplaces, logistics, dispatch, routing, mobility, delivery, or other real-time operational platforms.
• Experience with event-driven architecture, queues, streams, retries, and idempotent workflow design.
• Familiarity with cloud infrastructure and modern DevOps practices such as CI/CD, observability, deployment safety, and production monitoring.
• Strong interest in mentorship and building a culture of ownership, quality, and operational discipline.
• Familiarity with tools and systems such as Slack, Google Workspace, ChatGPT, ClickUp, Hubstaff, GitHub, Jira, Notion, cloud platforms, observability tools, CI/CD systems, and other engineering collaboration or delivery tools.
• Familiarity with AI workflows beyond chat interfaces, including coding agents, debugging agents, research agents, workflow automations, internal copilots, or AI-supported engineering assistants.

Why Join Muvr

• High ownership and real technical influence over platform direction and engineering standards.
• Opportunity to solve complex real-world logistics problems in a real-time marketplace.
• Work with a mission-driven, fast-moving team where engineering quality directly impacts customers and operations.
• Help shape scalable systems, stronger delivery practices, and long-term technical foundations.
• Competitive compensation.