Conquer AI
Senior/Lead - AI Intelligence Architect
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Senior/Lead Intelligence Architect (AI) 10 + Hires
Day Rate Contract | Remote (UK) | Ongoing, initially 12 to 24 months
Please note: You will be required to complete security checks for this deployment.
This role would suit you if you consider yourself an Engineer first and a Consultant second, someone who has carried a system from a client’s vague problem through to something running in production, written the code yourself rather than just directed it, and who is just as comfortable at the keyboard as in the room with senior stakeholders.
You might have gone by Forward Deployed Engineer, AI Systems Architect, or Principal/Staff AI Engineer perhaps even a CTO, OR CAIO, titles matter less to us than whether you have actually done the job, hands in the code and all.
About Conquer AI
Conquer AI designs and deploys AI systems for enterprise organisations. We don’t build for a slide deck. We build for production, and we deploy directly onto client sites, working inside their environments, their data and their existing infrastructure, so the system we ship is the system they actually run.
Our engineers also use DreamStack, our own platform, under licence with our clients.
That means our team sits close to the client throughout, not just at handover. Discovery, architecture, build and deployment all happen with real constraints in view: existing tech stacks, security requirements, live operational workflows.
The measure of success isn’t a demo. It’s whether the system is still running, still delivering value, months after we have shipped it.
The Role
You will take ambiguous, high-stakes client problems and carry them from discovery through to a system running in production. You won’t be handed a spec. You will build one, defend it to senior engineering and business stakeholders, and then build the thing itself.
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You will also be responsible for the DreamStack sessions you run with your clients.
What You Will Actually Do
- Run discovery directly with clients, often at VP or C-level, to turn a vague operational problem into a scoped technical approach
- Architect end-to-end AI systems across LLMs, data pipelines, APIs and workflow orchestration
- Configure and support DreamStack for your clients
- Lead DreamStack sessions with clients, from process discovery through system design to production code, with final say on what it proposes, accepts or rejects
- Make the build versus buy, and scope versus restraint, calls yourself, and own the consequences
- Work hands-on in the codebase as well as the architecture
- Lead and train other engineers on live delivery, not in the abstract
- Be the senior voice in the room when the engineering gets hard or the client gets nervous
Who We Are Looking For
This is a senior bar, and it’s a specific kind of senior. The strongest candidates have spent a decade or more doing enterprise or professional-services-style client delivery, often in regulated or compliance-heavy settings, before or alongside becoming AI specialists. That background matters as much as the AI skills do.
Experience
- 10+ years in software engineering or technical architecture, with a long, consistent career rather than a string of short stints
- A proven history of owning delivery end-to-end: discovery, architecture, build and production, not just execution inside someone else’s plan
- Experience leading and training other engineers while remaining hands-on in the code
- Background in enterprise consulting, professional services, or client-facing technical delivery, ideally with Fortune 500 or regulated-industry clients
- Comfortable holding high-level technical conversations with senior engineering staff and translating the same thinking for business stakeholders
- Demonstrated rigour in how you verify and document your own work, not just confidence that it works
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Technical Depth
- Deep, production-grade experience with LLMs, RAG and multi-agentic systems, not just API integration
- Strong engineering foundations across Python and TypeScript, with real architecture and systems design ability
- Experience with data pipelines, orchestration and the operational realities of running AI in production
- Cloud deployment experience (AWS, Azure or GCP) in containerised, production environments
Core skills: Python, TypeScript, RAG, LLMs, multi-agentic systems, AI systems architecture, data pipelines, workflow orchestration, cloud deployment (AWS/Azure/GCP), production AI evaluation and guardrails
What You’ll Get
- Ownership of complex, high-value problems from day one, not a ramp-up period
- Direct client exposure at a senior level, not filtered through account management
- A team that moves quickly, ships, and holds a high bar
- Work alongside other senior architects operating at this level with access to the most cutting edge technology in AI.
Please note, I personally review every CV, message and email I receive about our vacancies, but I can’t reply to everyone individually given how many applications we get. Thank you for applying and for your interest in working with us. It’s genuinely appreciated.
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