Leadership Engineer

Company Overview

Smallest.ai builds real-time intelligence systems that operate under strict latency, cost, and reliability constraints. The company focuses on small, fast, controllable language models designed for production environments rather than just demonstrations. Key focus areas include small language models, long- and short-term memory systems, streaming inference, and adaptive agent architectures. The company prioritizes developing smaller models that enable faster token processing while ensuring real memory usage.

Job Summary

The Leadership Engineer will be responsible for building and leading a world-class engineering organization that delivers high-quality products efficiently and earns customer trust through consistent and reliable outcomes. The role emphasizes a balance of speed and quality, ensuring that the engineering team can deliver meaningful products while maintaining high standards.

Responsibilities

• Delivery Machine: Lead planning, execution, reviews, and releases to ensure predictable output without chaos.
• Quality Bar: Define and enforce quality standards, including tests, performance, observability, and security while continuously improving them.
• People + Culture: Lead and mentor team members of varying seniority, fostering psychological safety and accountability while managing conflicts effectively.
• Technical Leadership: Make architectural decisions across backend, infrastructure, data, and machine learning systems, with a focus on reliability.
• Speed with Quality: Shorten cycle times while avoiding regressions, outages, or silent failures.
• Customer Trust: Promote a culture of incident response and root cause analysis (RCA), prioritizing reliability as a product.

Qualifications

• Leadership: Proven experience leading teams of mixed seniority and ensuring cohesive execution.
• Execution: The ability to deliver meaningful products in short time frames (days/weeks) with strong prioritization skills.
• Technical Breadth: Solid architectural judgment in distributed systems, APIs, data pipelines, and cloud infrastructure.
• Reliability + Observability: Experience building and operating production systems with Service Level Objectives (SLOs), alerting, dashboards, and incident response practices.
• Real-time / Low-latency Systems: Familiarity with streaming and real-time systems, including performance profiling and capacity planning.
• Startup Scaling Mindset: Experience in fast-scaling environments and the ability to scale teams and processes with minimal bureaucracy.
• Quality Obsession: Definition of “done” that includes tests, continuous integration (CI) gates, rollout plans, and documentation.
• Educational Qualifications: Relevant degree in Computer Science, Engineering, or related field.

Preferred Skills

• Experience shipping AI/machine learning systems in production, specifically large language models or speech pipelines.
• Security and compliance knowledge (e.g., SOC2/ISO, handling personally identifiable information (PII)).
• Background in hiring and establishing multi-team organizational structures.

Experience

• Prior experience in leadership roles within engineering, particularly in fast-paced or startup environments.
• Experience with managing production systems and team execution.

Environment

The specific work setting and location details are not provided. Flexibility regarding remote, in-office, or hybrid arrangements may be assumed.

Salary

Salary details are not specified.

Growth Opportunities

Opportunities to shape the culture of the engineering team and build the engineering organization from early stages are available.

Benefits

Information on benefits is not specified.