Senior AI-Native Software Engineer

VELOZIENT LLC
United States
11 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Query Performance Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Application Layers C Sharp (Programming Language) Mobile Application Development Software as a Service Code Review Databases Relational Databases Cursor (Graphical User Interface Elements)
+18 more
Software Debugging Distributed Systems Eclipse (Software) Python (Programming Language) Node.Js Object-Oriented Software Development Software Engineering Systems Integration TypeScript Manual Data Entry Multi-Agent Systems Backend Epicor ERP Front End Software Development Virtual Agents Service Stack Golang Programming Languages

Job description

Our client is building an AI-powered platform that transforms how wholesale distributors operate by embedding intelligent automation into the core workflows that drive product distribution. Serving a multi-trillion-dollar industry, the platform unifies customer relationship management, product information, eCommerce, and order and quote management into a single AI-driven ecosystem. By streamlining complex processes and reducing manual data entry, it enables sales teams to focus on delivering exceptional customer experiences and growing strategic relationships.

This is a generalist engineering role. Engineers are not siloed by frontend, backend, or specific programming languages. Instead, they are expected to apply strong engineering fundamentals, sound technical judgment, and AI-native development practices to solve problems across the product. You will work closely with Product Managers, designers, and other engineers to scope, build, and deploy features, while periodically partnering with customers during onboarding, troubleshooting integrations, and helping them get the most value from the platform. Occasional travel to customer sites a few times a year is expected.

Responsibilities

  • Own end-to-end delivery of features-from refining requirements to deployment, monitoring, and continuous iteration
  • Operate AI coding agents (Claude Code and similar) at a high level: scope work, structure context, orchestrate multiple agents when appropriate, and ship reviewed, production-quality software
  • Apply strong software engineering fundamentals to design scalable architectures, APIs, databases, and integrations, regardless of the underlying technology stack
  • Move fluidly across different technologies and application layers, learning and adapting as needed to solve business problems
  • Collaborate in a squad model with PMs, designers, and engineers; participate in two-week sprints, standups, refinements, retrospectives, and code reviews
  • Ensure performance, reliability, maintainability, and correctness of the systems you build-the responsibility for technical quality remains with the engineer, not the AI agent
  • Contribute to engineering best practices, developer tooling, and AI-native development workflows across the team
  • Spend time with customers onsite a few times a year to better understand their operational challenges and improve product decisions

Requirements

We are seeking a full-time, remote Senior AI-Native Software Engineer with 5+ years of professional software engineering experience to join our U.S. client. In this role, you will own end-to-end feature delivery across the software development lifecycle while leveraging AI coding agents as a first-class collaborator to scope, build, validate, and ship production-quality software at high velocity., * Excellent English communication skills

  • 5+ years of professional software engineering experience delivering production software with real users and real ownership
  • Strong object-oriented programming fundamentals and the ability to quickly become productive in different programming languages and technology stacks
  • Daily, hands-on experience using AI coding agents such as Claude Code, Cursor Agent, Codex, or similar to ship production software-not just for autocomplete, but as an integral part of the development workflow
  • Ability to explain how you structure prompts, manage context, orchestrate AI agents, validate generated code, and determine when AI output requires correction
  • Strong software engineering fundamentals, including the ability to debug production issues, analyze stack traces, reason about query performance, identify concurrency problems, and troubleshoot distributed systems
  • Experience designing APIs, relational databases, data models, and software integrations
  • Generalist mindset with the ability to work across different parts of the application rather than specializing exclusively in frontend or backend development
  • Startup mindset: pragmatic, adaptable, comfortable with ambiguity, and biased toward delivering customer value quickly
  • Strong communication skills with the ability to explain technical decisions to engineers, product managers, designers, and customers
  • Ownership and sound engineering judgment, with the ability to independently take features from concept to production while making thoughtful tradeoff decisions
  • Proven delivery experience in a fast-paced startup environment
  • A collaborative approach, a can-do attitude, and a relentless drive to solve problems
  • Trustworthy, team-oriented, and transparent

Desired Experience

  • University degree or equivalent professional software engineering experience
  • Experience with modern object-oriented languages such as Python, TypeScript/Node.js, Java, C#, Go, or similar
  • Experience building integrations with distribution ERPs (Epicor Eclipse, P21, or similar), including ingesting orders, products, customers, and pricing while reconciling complex real-world data
  • Experience building or integrating with agentic products, including MCP servers, tool-using agents, agent frameworks, evaluation frameworks, or prompt and context engineering at the system level
  • Prior experience at an early-stage SaaS startup

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