Senior Backend Developer

About the role

BLP Digital builds agentic AI for enterprise ERP automation, and this role is centered on designing and delivering software that drives automation across finance, procurement, logistics, and sales. You will own the implementation within dedicated product teams that have full responsibility for their roadmap and the business impact they generate. This position requires you to translate complex business requirements into robust backend solutions that are reliable, scalable, and production-ready. You will work closely with cross-functional partners to ensure that the software you build directly supports enterprise-level automation goals. A large portion of your time will be spent on design, code review, debugging, and collaboration, not just writing new code from scratch. Your ability to explain intricate technical decisions in clear, non-technical language will be a key factor in your success. Ultimately, you will be responsible for shaping the technical direction of major initiatives while ensuring that the final product meets strict standards of quality and performance.

Key facts

What you'll do

Convert business requirements from stakeholders into concrete product improvements through close collaboration with product owners and domain experts.

Design, develop, and maintain clean, maintainable, and high-quality backend software to serve demanding enterprise automation needs across multiple domains.

Participate in and elevate technical excellence through consistent and constructive code reviews that share knowledge and improve the overall engineering standard.

Provide technical direction for major initiatives and mentor team members throughout the product journey to ensure alignment with long-term goals.

Break down complex systems and intricate business ideas into clear, understandable components that can be implemented effectively by the team.

Balance cost and benefit while staying aligned with team and company goals, ensuring that every decision supports the broader business strategy.

Take end-to-end responsibility for technical work, the product outcomes, and the ongoing health of the team's architecture and processes.

Simplify complexity in both systems and communication, enabling stakeholders and engineers to understand trade-offs and make informed decisions.

Contribute to an evolving tech stack and support continuous improvement initiatives that help the engineering organization grow and adapt.

Ensure that all implemented solutions are production-grade, secure, and performant under real-world enterprise conditions.

Collaborate with data and machine learning teams to integrate intelligent automation features into the backend services.

Work within containerized and orchestrated environments on cloud infrastructure such as GCS, AWS, or Azure to support scalable deployments.

Engage in the full lifecycle of software delivery, including requirements refinement, implementation, testing, and ongoing optimization.

Act as a technical owner who proactively identifies risks, proposes solutions, and drives resolution across the product and engineering teams.

Requirements

Hold a Bachelor's or Master's degree in Computer Science or possess equivalent practical experience that demonstrates the same level of competence.

Bring five or more years of professional software engineering experience with a proven track record of delivering production systems.

Show a strong understanding of software craftsmanship, Clean Code principles, and Clean Architecture patterns in your daily work.

Demonstrate the ability to translate business problems into precise requirements, specifications, and high-quality code.

Consistently write tests and ensure that your daily work supports both team and company goals while balancing cost and benefit.

Take responsibility not only for technical work but also for the product direction and the shape of the team's contributions.

Simplify complex systems and communicate complex ideas clearly to both technical and non-technical audiences.

Work authorization is required for the Zurich-based position, and you must be able to operate within the local legal and regulatory framework.

Nice to have

Contribution to an evolving tech stack and support for continuous improvement initiatives is welcomed as part of the team's collaborative culture.

Skills & tools

Practical experience with backend programming languages commonly used in enterprise environments.

Familiarity with cloud platforms such as GCS, AWS, or Azure and infrastructure-as-code practices.

Knowledge of containerization and orchestration tools that manage application lifecycle in production.

Understanding of data platforms and how machine learning models can be integrated into backend services.

Experience working in agile environments with sprints, daily standups, and iterative delivery practices.

Practical notes

Work authorization is required for the Zurich-based position.

The role operates within dedicated engineering teams with end-to-end ownership of products and features.

Typical interview steps for engineering roles usually start with a recruiter screen, followed by one or two technical rounds.

Candidates often solve a coding problem, discuss past projects, and answer system design questions during the process.

Some rounds may include a take-home task to assess practical implementation skills.

Final rounds typically focus on team fit and provide candidates with an opportunity to ask questions about the role and the organization.

Interviewers evaluate how you break down unfamiliar problems, rather than only whether you arrive at the correct answer.

Practicing a few problems aloud and reviewing your own past projects is among the best ways to prepare for the interviews.

Good to know

Agentic AI automates business processes using autonomous decision-making components that operate with minimal human intervention.

Cloud infrastructure on GCS, AWS, or Azure supports scalable deployment and resilient service delivery.

Containerization and orchestration tools manage the full lifecycle of applications in production environments.

Data platforms and machine learning models enable intelligent automation and enhance backend decision-making capabilities.

Questions to ask

Good questions to ask the employer in the interview include what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how decisions are made within the group.

Asking about growth paths and the review process is also well received and demonstrates long-term interest in the role.

Employers expect candidates to ask questions, and well-prepared questions show that you have done your research.

Career growth

Engineering careers typically progress from individual contributor to senior, staff, and principal levels as impact and scope increase.

Some engineers move into management and lead teams of five to twenty people, while others remain on the technical track.

Growth is driven by demonstrated impact rather than tenure alone, and consistent delivery plays a major role in progression.

A typical engineering ladder has clear levels with defined expectations for scope, quality, mentorship, and ownership.

Moving up usually requires taking on end-to-end responsibility for outcomes rather than simply completing assigned tickets.