Software Engineer, Product
M
Mackin TalentAI software
UK RemoteContractSenior
Salary not disclosed
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Job Details
- Experience
- 6+ years of experience building production software in software engineering, product engineering, ML engineering, or a hands-on technical solutions role.
- Required Skills
- PythonJavaC++RESTful APIs
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- 6+ years of experience building production software in software engineering, product engineering, ML engineering, or a hands-on technical solutions role.
- Experience independently owning scoped technical products from an ambiguous problem through design, implementation, launch, and iteration.
- Proficiency in one or more general-purpose programming languages, such as Python, JavaScript/TypeScript, Java, PHP/Hack, or C++.
- Experience building or integrating APIs, backend services, data workflows, or full-stack products, including debugging complex integration issues.
- Experience applying production engineering practices such as automated testing, observability, actionable errors, and safe failure handling.
- Experience using data and metrics to evaluate outcomes and communicating technical concepts and trade-offs to technical and non-technical stakeholders.
- Preferred: Experience building or integrating AI/ML-enabled products, evaluation systems, or agentic workflows.
- Preferred: Experience building internal tools, developer platforms, or reusable self-service capabilities.
- Preferred: Product judgment or experience translating user feedback into actionable engineering requirements.
- Preferred: Experience using AI-assisted development or LLM-based systems to improve engineering velocity or redesign operational workflows, while reviewing and validating the resulting work.
- Preferred: Experience contributing to shared codebases using version control, code review, automated testing, and documented engineering practices.
Responsibilities
- Partner with technical and non-technical users to understand problems, desired outcomes, and constraints.
- Build end-to-end internal products, integrations, and data workflows.
- Turn prototypes and one-off solutions into reliable, reusable capabilities.
- Design evaluation and feedback loops for AI-powered workflows.
- Apply production engineering practices, including testing, observability, actionable errors, and safe failure handling.
- Use AI coding tools thoughtfully and review and validate generated work.
- Measure adoption, quality, time saved, and reduction in manual support.
- Create documentation and onboarding paths for users and engineers.
- Own and prioritize technical workstreams, making trade-offs based on impact and complexity.
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