Senior Product Software Engineer - AI Native

Description

The company provides expert software and information solutions that leading professionals depend on at critical moments.

The company is hiring a Senior Product Software Engineer - AI Native to join an existing team.

You will take software solutions from the first discovery stage through to live production, turning customer, business and technical needs into dependable, secure, scalable and maintainable products.

You will work on team-level problems that are not yet well defined, coordinating with many stakeholders to set requirements, shape approaches and deliver results.

You will use approved AI-assisted development and automation tools where they fit, and stay answerable for the quality, correctness, security and operational readiness of everything you approve or release.

You act as a technical go-to person for the team and help less experienced engineers grow.

Responsibilities

• Own solutions end to end, turning customer, business and technical requirements into outcomes that hold up over time.
• Clarify unclear requirements, set objectives, compare options and choose a solution direction.
• Design, build, test, deploy, maintain and improve applications, services and platforms, using direct coding or approved AI-assisted methods.
• Apply approved AI techniques while checking their output and keeping responsibility for architecture, quality, security and operational readiness.
• Write down requirements, design choices, acceptance criteria, dependencies, risks and implementation notes.
• Choose and carry out testing and verification suited to each piece of work's complexity, risk and business impact.
• Guide others through design reviews, code reviews, knowledge sharing, mentoring and sound engineering practice.
• Find and fix problems that span components, occur in production or affect the whole system, and put lasting fixes in place.
• Build security, privacy, compliance and data protection into every stage of the lifecycle.
• Work with product, design, architecture, operations, security and business colleagues to shape solutions.
• Raise performance, scalability, reliability, resilience and maintainability while lowering operational risk.
• Improve engineering processes, delivery speed and team skills through automation, standards and shared learning.
• Weigh customer impact, product strategy, operational effects and business outcomes when making technical decisions.
• Use specifications and evaluation criteria to guide ambiguous work, supply context and constraints, check generated output, and teach others to use AI responsibly.
• Treat all AI-generated output as unverified until it has been reviewed and validated in line with its risk.
• Decide what testing and validation a given area needs, and confirm that solutions meet quality, reliability, security, compliance and operational expectations.
• Define and assess acceptance criteria, produce evidence that work is ready for production, and identify, manage and escalate technical risks.

Requirements

• Bachelor's degree in a relevant field, or equivalent demonstrated experience (required).
• 4-6 years of relevant experience in product software engineering (required).
• Strong experience as a full stack software engineer.
• Advanced knowledge of C,.NET Framework,.NET Core, ASP.NET Web API, Angular, RESTful APIs, microservices architectures, SQL, relational database design and Redis.
• Working knowledge of asynchronous messaging systems such as RabbitMQ, MassTransit and Azure Service Bus.
• Solid understanding of object-oriented programming, SOLID principles, Domain-Driven Design and clean code practices.
• Ability to design, build and maintain software by applying computer science principles, understand user needs, and test and fix issues.
• Ability to produce working software whether you write it, direct approved generation tools, or review and take responsibility for contributed code, including reading, tracing and diagnosing any code.
• Ability to turn customer needs, business goals and product intent into clear, testable specifications that align stakeholders, reduce ambiguity and guide AI-assisted development.
• Ability to understand complex situations, break them into parts, define the problem and pick the most effective course of action.
• Ability to test systems and processes to find problems, measure effectiveness and confirm quality.
• Ability to respond quickly and well to change, with a focus on continuous improvement and flexible planning.
• Ability to work in a shared codebase using branching, review and merge practices, and to keep a clean, meaningful history.
• Ability to design, implement and query relational databases, including SQL and sound database design.
• Ability to design, build and manage APIs, including their documentation, security and testing.
• Ability to structure software so it is clear, changeable, secure, operable and fit for purpose, including interfaces, contracts, patterns and testability.
• Ability to write clear, current and useful technical documentation.
• Ability to apply application security controls covering secure coding, access control, authentication and security testing.
• Competencies: strong ownership, speed that comes from removing friction, inventive solutions with large impact, engineering leverage through tools and automation, AI-first thinking, fast learning, respectful challenge of assumptions, balancing technology with market realities, raising team standards, enterprise-wide thinking, sharp prioritisation, thoughtful risk-taking, inclusive collaboration, alignment of individual and team goals, logical problem solving, current domain knowledge and operational precision.

Conditions

Hybrid work model.

Applicants may be required to attend an onsite interview at a company office as part of recruitment.

Candidates must complete interviews without AI tools, external prompts or virtual backgrounds, and in-person interviews are part of the process; using AI-generated answers or outside help in interviews leads to disqualification.