Next Step Systems - National IT Recruiting Firm

Engineering Manager

• Own the application engineering strategy and execution across backend, mobile, and desktop
• Lead and grow a small, senior applications team, including backend, mobile, and desktop engineers
• Set the architectural direction for Artificial Intelligence (AI)-powered product workflows, APIs, and client integrations
• Ensure AI capabilities are integrated into the product with clear abstractions, predictable behavior, and graceful failure modes
• Partner closely with Machine Learning leadership to translate model capability into shippable product features
• Make high-impact decisions across latency, cost, reliability, security, and user experience
• Establish clear ownership boundaries across backend, mobile, and desktop to prevent architectural drift
• Ensure production readiness through observability, monitoring, retries, fallbacks, privacy, and cost controls
• Balance speed and discipline by shipping quickly without compromising long-term system quality

VP of Engineering Applications, Artificial Intelligence

Technical Product Manager

• Research and define end-to-end Artificial Intelligence (AI) system requirements from capability to behavior to user impact
• Translate model capabilities, data constraints, and evaluation results into clear product and system decisions
• Make trade-offs across quality, latency, cost, reliability, and UX
• Work closely with Machine Learning (ML), backend, and mobile engineers on system design, evaluation, and iteration
• Define and evolve evaluation frameworks across offline metrics, online experiments, and human feedback
• Drive execution with clear specs, strong judgment, and disciplined prioritization
• Ensure systems ship quickly, safely, and reliably, with strong feedback loops
• Own product quality end-to-end, including correctness, predictability, and user trust
• Align AI capabilities with user needs and company priorities
• Establish clear roadmaps and priorities and enable fast iteration based on user feedback
• Keep teams aligned and focused on AI product goals

Technical Product Manager, Artificial Intelligence (AI) Systems

AI Engineer

• Own the application engineering strategy and execution across backend, mobile, and desktop
• Design reliable systems for AI-powered workflows, including state, orchestration, tool use, retries, fallbacks, and failure handling
• Build APIs and abstractions connecting AI systems to real-world product experiences
• Lead a small, senior engineering team through design reviews, code reviews, and hands-on mentorship
• Make high-impact trade-offs across latency, reliability, cost, security, and user experience
• Establish production foundations including observability, monitoring, testing, and operational excellence
• Partner with Machine Learning leadership to turn model capabilities into robust, shippable product experiences
• Keep architecture simple, maintainable, and ready to scale
• Deliver observable, monitored, stable production systems
• Improve latency and reliability measurably over time

Principal Software Engineer, AI Email Applications, Artificial Intelligence

• Own application engineering strategy and execution across backend, mobile, and desktop
• Design reliable systems for AI-powered workflows, including state, orchestration, tool use, retries, fallbacks, and failure handling
• Build APIs and abstractions connecting AI systems to real-world product experiences
• Lead a small, senior engineering team through design reviews, code reviews, and hands-on mentorship
• Make trade-offs across latency, reliability, cost, security, and user experience
• Establish observability, monitoring, testing, and operational excellence foundations
• Partner with Machine Learning leadership to turn model capabilities into robust, shippable product experiences
• Keep architecture simple, maintainable, and scalable
• Deliver observable, monitored, stable production systems
• Improve latency and reliability measurably over time

Engineering Lead, AI Email Applications

• Own application engineering strategy and execution across backend, mobile, and desktop
• Design reliable systems for AI-powered workflows, including state, orchestration, tool use, retries, fallbacks, and failure handling
• Build APIs and abstractions connecting AI systems to real-world product experiences
• Lead a small, senior engineering team through design reviews, code reviews, and hands-on mentorship
• Make trade-offs across latency, reliability, cost, security, and user experience
• Establish production foundations including observability, monitoring, testing, and operational excellence
• Partner with Machine Learning leadership to turn model capabilities into robust, shippable product experiences
• Keep architecture simple, maintainable, and ready to scale
• Deliver observable, monitored, stable production systems
• Improve latency and reliability measurably over time

Staff Software Engineer, AI Email Applications, Artificial Intelligence

Chief Technology Officer

• Define the long-term architecture for AI systems, infrastructure, and developer platform
• Evaluate trade-offs between speed of iteration and long-term system design
• Ensure systems are designed for scalability, reliability, and long-term evolution
• Guide decisions across model integration, data pipelines, distributed systems, and product architecture
• Translate product direction into clear technical execution with engineers
• Structure engineering workstreams and align teams on priorities
• Maintain high engineering standards while focusing on shipping
• Establish engineering culture, development practices, and technical standards
• Build and scale an engineering team across China and the US
• Identify technical leaders and build a high-quality engineering organization
• Define hiring standards and interview processes
• Collaborate with product, research, and leadership teams
• Coordinate technical workstreams across teams and locations
• Resolve cross-team technical and execution challenges

Chief Technology Officer, Artificial Intelligence

Lead Software Engineer, AI Email Applications, Artificial Intelligence

Machine Learning Engineer

• Set and evolve the research direction for core intelligence, including context representation, memory, reasoning, planning, and orchestration
• Decide when to design new model architectures versus adapting or leveraging frontier open-source or commercial models
• Define evaluation frameworks measuring real-world usefulness, robustness, safety, and long-term behavior
• Own alignment, safety, and guardrail strategy as first-class product concerns
• Guide exploration of retrieval-augmented training, mixture-of-experts, distillation, multi-agent orchestration, and multimodal systems
• Shape early product intelligence direction in close partnership with product and application engineering
• Set the technical bar for research rigor, judgment, and taste across the organization