OUR HIRING PROCESS:
- We will review your application against our job requirements. We do not employ machine learning technologies during this phase as we believe every human deserves attention from another human. We do not think machines can evaluate your application quite like our seasoned recruiting professionals—every person is unique. We promise to give your candidacy a fair and detailed assessment.
- We may then invite you to submit a video interview for the review of the hiring manager. This video interview is often followed by a test or short project that allows us to determine whether you will be a good fit for the team.
- At this point, we will invite you to interview with our hiring manager and/or the interview team. Please note: We do not conduct interviews via text message, Telegram, etc. and we never hire anyone into our organization without having met you face-to-face (or via Zoom). You will be invited to come to a live meeting or Zoom, where you will meet our INFUSE team.
- From there on, it’s decision time! If you are still excited to join INFUSE and we like you as much, we will have a conversation about your offer. We do not make offers without giving you the opportunity to speak with us live.
INFUSE is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our
We are looking for an AI & Software Solutions Architect to guide architectural decisions across INFUSE’s products and teams. You will review solutions built by internal teams and external vendors, establish shared engineering standards, guide legacy modernisation, and help ensure that production AI systems are reliable, secure and cost-effective.
As the Software Development department’s sole Solutions Architect, you will report directly to the Director of Technology and work across a landscape of 500+ repositories, including backend services, LLM-based products and several legacy systems requiring ongoing modernisation. This is a senior individual contributor role with company-wide technical influence and no direct people management. Success in this role depends on strong technical judgement, clear communication and the ability to influence engineering decisions across teams. Your work will centre on architecture, reviews and cross-project improvements, alongside prototypes and selected hands-on development tasks. Engineering teams will deliver the broader implementation.
What you will do:
- Translate business needs into architectural decisions, explaining trade-offs, costs and risks and balancing technical quality with delivery priorities.
- Review code, architecture and vendor deliverables. Produce concise, actionable findings, prioritise improvements, and verify that critical issues have been resolved.
- Establish shared standards across projects, including security, documentation, service contracts and observability, and guide teams in adopting them.
- Define guardrails for production LLM and agentic systems, covering evaluation, prompt management, model routing, multi-provider access, security and cost control.
- Guide legacy modernisation initiatives, including application decomposition, authorisation modernisation, workflow migration and safe transition planning.
- Work with engineering and DevOps teams to advance Kubernetes adoption, improve deployment workflows and observability, and diagnose architectural bottlenecks.
- Build prototypes and reference implementations to validate decisions, and conduct technical interviews for engineering hires.
What you will bring:
- 5+ years in software engineering, including 3+ years owning architectural decisions for production systems as an architect, principal engineer or technical lead, with experience taking solutions from initial concept through implementation to production.
- Strong computer science and system design fundamentals for scalable, high-load distributed systems, including reliability, failure handling, observability and architectural trade-offs.
- Hands-on AWS experience designing and running production services, plus practical Kubernetes experience and the ability to work closely with DevOps on deployment and operational improvements.
- Experience delivering production LLM-based solutions, with an understanding of their lifecycle from business need and design through implementation and operation. Relevant experience includes RAG, tool calling, multi-provider integrations and cost optimisation.
- Experience evaluating and monitoring LLM systems across quality, latency and cost using observability and evaluation tooling such as Langfuse or similar platforms.
- Experience reviewing other teams’ code and architecture and guiding legacy modernisation or migrations.
- A strong software engineering background, preferably with substantial Python and/or Node.js experience, and the flexibility to review and work across different stacks, including legacy PHP.
- Experience with PostgreSQL and NoSQL design and query optimisation, and asynchronous, event-driven systems using Kafka, RabbitMQ or similar brokers.
- Practical experience using agentic coding tools such as Claude Code, Codex or similar, with sound judgement about verifying generated code and assessing proposed changes.
- Clear technical writing and communication with engineers and non-technical stakeholders. You connect technical decisions to business goals, cost, risk and measurable outcomes, take responsibility for their consequences, and adjust your approach based on evidence.
- B2 or higher English for collaboration with distributed teams.
Nice to have:
- Experience with AIOps: applying AI to operational workflows, including anomaly detection, alert correlation, incident triage and observability.
- Understanding when classical ML is more appropriate than an LLM, and experience with MLOps.
- Experience with Keycloak or Azure AD SSO migrations.
- Experience with Backstage.
- Experience conducting vendor delivery audits.
- AWS Solutions Architect – Professional or Anthropic Claude certification.
We offer:
- We offer a competitive salary tailored to the candidate's experience and skills. Payments are processed monthly (USD)
- Full Remote. Work schedule: Monday-Friday, from 1:00 pm to 9:00 pm EEST (incl. 60-min breaks)
- Opportunity to work with cutting-edge AI and cloud solutions
- Access to the latest AI tools and premium subscriptions
- Long-term B2B collaboration
- Paid sick leave, vacation, and public holidays
- Reduced Fridays during the summer
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