Optimyze Consulting
Senior Software Engineer
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About the Client
Our client is an early-stage technology company building autonomous security technology at the intersection of AI and cybersecurity.
The company is developing AI agents that can perform complex security testing and assessment workflows, with the product already being used by enterprise customers.
The engineering team is small. Engineers therefore have direct ownership of what they build, how it is deployed, and how it performs once it is running in production.
About the Role
This role is for a hands-on Senior Software Engineer who has a strong track record of building and running software in production.
The key requirement is not simply experience with particular technologies. We are looking for someone who has personally taken software from an initial technical problem, through design and implementation, into a live production environment, and remained involved in operating and improving it afterwards.
You will be writing code, making architectural decisions, deploying systems, investigating failures, and improving software as it runs at scale.
Python is the primary engineering language. The role also involves AWS, cloud infrastructure, containers, and Infrastructure as Code, alongside distributed systems and AI-native development.
What You’ll Actually Be Doing
- Build backend software in Python and remain directly involved in the codebase.
- Take ownership of systems from technical design through implementation, deployment, and production operation.
- Design and build services that need to be reliable, scalable, and resilient under real workloads.
- Diagnose and resolve problems in live systems rather than handing production issues over to another team.
- Improve existing production systems as requirements, scale, and technical constraints evolve.
- Work directly with AWS and the infrastructure supporting the applications you build.
- Build and manage infrastructure using Terraform and Infrastructure as Code.
- Work with containers and modern deployment environments.
- Design systems involving distributed processing, asynchronous workloads, concurrency, or long-running workflows.
- Contribute to the development of AI-driven systems and agentic workflows.
- Help make AI systems observable, traceable, and testable when running in production.
- Make pragmatic architectural decisions and contribute to engineering standards in a small team.
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What We’re Looking For
The most important part of this role is proven hands-on software engineering experience.
You should be able to demonstrate that you have:
- Personally written substantial amounts of production software as a professional Software Engineer.
- Taken ownership beyond coding, including technical design, implementation, deployment, and operation.
- Worked with software after it went live, including debugging production issues, investigating failures, and improving reliability or performance.
- Strong professional Python experience. Python should be a language you have actually used to build software, not simply a technology listed on your CV.
- Built backend services, APIs, or other software systems that were used by real customers or internal users.
- Worked with AWS and cloud infrastructure in a hands-on capacity.
- Worked with Docker or similar container technologies.
- Used Terraform or another Infrastructure as Code approach to provision and manage infrastructure.
- A solid understanding of SQL and relational databases.
- Experience with systems where reliability, scalability, concurrency, or distributed processing mattered.
- A strong security mindset and an understanding of how security considerations affect software and infrastructure design.
- The autonomy to investigate a problem, determine the appropriate technical approach, and take it through to a working solution.
AI & Security
You do not need to be a cybersecurity specialist or an AI researcher.
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The core of the role is software engineering.
However, the product sits at the intersection of AI and cybersecurity, so experience in either area is particularly relevant.
This could include:
- Building AI agents or LLM-powered applications
- Agent orchestration or tool calling
- Designing evaluation, observability, or traceability for AI systems
- Cybersecurity or security engineering
- Offensive security, penetration testing, bug bounty, or CTF experience
- Secure application or infrastructure design
Particularly Relevant Experience
The following would strengthen your background further:
- Distributed systems and asynchronous processing
- Event-driven architectures
- Kubernetes
- Terraform
- Production observability with tools such as Grafana, Prometheus, or OpenTelemetry
- Distributed workflow or durable execution systems
- Multi-tenant SaaS
- Scaling or re-platforming existing production systems
- Experience working in a small engineering team where you owned significant parts of the technical solution
- Early-stage or founding engineering experience
A Good Fit for This Role
This role is particularly suited to an engineer who enjoys building rather than simply designing, and who wants to remain close to the technical execution.
You should be comfortable being the person who writes the code, deploys it, sees something fail in production, investigates why, fixes it, and improves the system afterwards.
The environment is early-stage and technically ambitious, so there is considerable scope to influence architecture and engineering practices. At the same time, the expectation is that senior engineers remain deeply hands-on and accountable for the software they build.
Location: London, with 3 days per week in the office.
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