Who We Are:
Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.
About the Product:
This is a hyper-scale fintech platform trusted by over 40 million users worldwide, offering access to multi-asset trading β including stocks, indices, currencies, and digital assets.
The product operates as a regulated, data-intensive financial ecosystem, processing massive volumes of transactions and real-time customer interactions daily. Itβs well-funded, profitable, and known for pushing innovation in AI, automation, and data governance across its operations. Advertising presence is strong (especially in the UK), but behind the scenes is a serious engineering culture solving hard, real-world problems at scale.
About the Role:
This is a hybrid role where youβll act as both the architect for complex BizOps initiatives and the leader of the integration engineering team, guiding the implementation of your blueprints and driving hands-on decisions with internal platforms.
Youβll report directly to the Director of BizOps, shaping architecture for AI-first automation, overseeing API and integration patterns, and ensuring alignment across cross-functional domains like security, IT, compliance, trading, and customer support.
This isnβt about maintaining legacy systems. Youβll design new architectures from scratch, define standards, challenge assumptions, and build a reusable platform of services that internal teams can scale on.
Every initiative touches multiple business domains β from R&D to Data to Security. You wonβt be siloed into one stack, tool, or domain. Youβll be trusted to make end-to-end architectural calls, balance technical elegance with delivery, and operate as a multiplier across the company.
Key Responsibilities:
Architecture & Design
- Own the technical architecture of internal BizOps platforms β spanning applications, integrations, and automation systems.
- Design scalable, modular solutions that serve diverse business domains (compliance, support, trading, finance).
- Define and evolve the companyβs AI architecture: from RAG pipelines and agent orchestration to latency, security, and performance design.
- Build reusable frameworks for APIs, data pipelines, and internal automation β with strong observability and operational hygiene.
- Ensure every design balances delivery speed with long-term scalability and cost-efficiency.
Leadership & Collaboration
- Lead a compact, senior Integration Engineering team β set direction, review architecture, and guide delivery.
- Provide architectural guidance across BizOps squads; coach developers and unblock projects.
- Collaborate cross-functionally with BAs, solution architects, data teams, R&D, and security to align architecture with business needs.
Integration & Data Ownership
- Own architecture and delivery of integrations β internal tools, external APIs, CRM, data lake, and BI pipeline.
- Design integration patterns (event-based, ETL, real-time) that serve business-critical workflows.
- Drive automation and orchestration across teams using data-driven and AI-enhanced designs.
Governance & Continuous Improvement
- Define development standards and architecture review processes across BizOps engineering.
- Ensure security, compliance, and reliability across systems and integrations.
- Bring in new tools, frameworks, or platforms when they accelerate the teamβs ability to deliver smarter and faster.
Required Competence and Skills:
- 7+ years designing and owning application or platform architecture across multiple domains.
- Proven experience building and scaling internal or product platforms serving multiple teams or business units.
- Strong hands-on system design capability β able to design practical, production-ready solutions (not just conceptual diagrams).
- Experience in designing and delivering AI-driven systems in production.
- Hands-on experience with LLM-based solutions such as RAG pipelines, agent-based architectures, orchestration, and performance considerations.
- Ability to explain architectural trade-offs in AI systems (latency, cost, reliability, hallucination handling, observability).
- Defined integration architecture patterns across multiple systems or domains (API-based, event-driven, real-time, ETL).
- Comfortable working in integration-heavy environments (CRM, data platforms, internal tools, external APIs).
- Strong understanding of full application lifecycle (backend, frontend, data, testing, orchestration).
- Experience designing systems that support real business workflows (Ops, Finance, Risk, Compliance, Support, etc.).
- Ability to translate business problems into scalable architectural solutions.
- Thrives in fast-moving environments and can bring structure to evolving systems.
- Comfortable balancing delivery speed with long-term scalability and cost-efficiency.
Nice to have:
- Experience in regulated industries (FinTech, compliance-heavy environments).
- Exposure to enterprise platforms (Salesforce, MuleSoft, Databricks, Azure, etc.).
- Experience designing internal developer platforms or AI frameworks.
- Strong build-vs-buy evaluation experience.