Senior Production & Platform Engineer

Lornets works with organisations when software has become commercially or operationally important and the engineering underneath it needs to be understood, strengthened or changed.

Our work spans production assurance and engineering, technical readiness, platform transition and systems moving into more demanding operational environments.

We are looking for experienced engineers who can move comfortably between technical assessment, engineering judgement and hands-on production work.

You will enter systems you did not design and establish how they actually work.

That may mean tracing application behaviour through code, data, infrastructure and external dependencies; assessing a product ahead of enterprise growth or technical diligence; diagnosing reliability or scalability problems; strengthening an increasingly critical platform; or executing an architectural or platform transition where the evidence justifies one.

You will be expected not only to identify weaknesses, but also to distinguish material engineering risk from acceptable technical debt and determine what level of intervention is proportionate.

Where remediation is required, you should be capable of implementing it or technically leading the engineers who do.

This is not a narrow infrastructure, cloud administration or DevOps role. You will work across the system.

You should be an experienced software, production or platform engineer with substantial experience operating real systems in production.

Strong candidates will usually have depth across several of the following:

• Backend and distributed systems
• Application and system architecture
• APIs and service integration
• Relational and non-relational databases
• AWS, Azure or GCP
• Containers and infrastructure as code
• CI/CD and release engineering
• Observability and incident investigation
• Reliability and disaster recovery
• Performance and scalability
• Authentication, authorisation and application security fundamentals
• Migrations and platform modernisation

You do not need to match a particular technology stack.

We care considerably more about whether you can understand an unfamiliar system, reason from evidence and make good engineering decisions.

You should be comfortable reading and working with production application code, not only the infrastructure around it.

You should also be capable of moving between diagnosis and implementation. Some engagements will require an assessment and clear technical conclusions. Others will require you to stay involved and help execute the changes you recommend.

Strong written communication is important. Part of the work is explaining what the evidence shows, why it matters, what should happen next and what does not need to change.

We value engineers who understand commercial context as well as technical possibility. The technically most sophisticated solution is not automatically the right solution for the client.

Lornets does not begin with the assumption that an existing system needs to be rebuilt.

Our principle is: Assess first. Keep what works. Change only what the evidence justifies.

You should know when to preserve something, when to strengthen it, when to refactor it and when replacement is genuinely justified.

You should be equally comfortable telling a client that something is good enough when the evidence supports that conclusion.

Assessment should not become a mechanism for manufacturing implementation work.

Engineers working with Lornets are expected to preserve independence in their technical judgement and make recommendations proportionate to the evidence, the risk and the client's actual situation.

Because this is initially an associate role, the amount of work may vary between engagements. We want to build long-term relationships with a small number of senior engineers whom we can involve repeatedly as the client portfolio grows.

Send us your CV or LinkedIn profile and briefly describe one production system you had to understand, diagnose or strengthen.

Tell us:

• What initially appeared to be wrong
• How you established how the system actually behaved
• What evidence you gathered
• Whether the evidence changed your original view
• What you ultimately recommended or implemented

We are particularly interested in examples where the right answer was more nuanced than simply rebuilding the system.