Jobgether
Engineering Manager - AI Product

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Engineering Manager – AI Product
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engineering Manager – AI Product based in the United Kingdom.
Join an opportunity to lead the development of a cutting-edge AI platform that powers innovative products at scale. This role combines technical leadership with hands-on engineering, offering the chance to shape architecture, mentor a talented team, and contribute directly to production-grade AI systems. Working in a collaborative, remote-first environment, you will drive the evolution of modern AI infrastructure while balancing strategic decision-making with active software development. If you enjoy building high-performance AI platforms, leading by example, and delivering meaningful impact in a fast-paced setting, this role offers an exciting next step in your career.
Accountabilities
- Lead, mentor, and develop a small team of AI engineers, fostering a culture of ownership, collaboration, and engineering excellence.
- Define the technical vision and architectural direction of the AI product, ensuring high standards for performance, scalability, reliability, and cost efficiency.
- Contribute hands-on to the design, implementation, and optimization of production AI systems, including model serving, inference pipelines, retrieval systems, orchestration, and evaluation frameworks.
- Oversee the end-to-end AI platform, including GPU infrastructure, model deployment, versioning, embedding pipelines, monitoring, and quality evaluation processes.
- Collaborate closely with Product, Infrastructure, Security, and Backend teams to align priorities, deliver integrated solutions, and support strategic business goals.
- Conduct regular performance reviews, coaching sessions, and technical mentoring while translating long-term objectives into clear execution plans and ensuring successful project delivery.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
- 7+ years of experience in software engineering, including at least 2 years in an engineering management or technical leadership role.
- Proven experience building and operating production AI/ML platforms or inference infrastructure, with expertise in model serving, GPU workloads, latency optimization, and cost management.
- Strong backend engineering skills, including Python proficiency and experience with distributed systems; knowledge of Go, Rust, or similar languages is considered an advantage.
- Hands-on experience with modern LLM technologies, including model APIs, open-weight models, serving frameworks, vector databases, retrieval systems, and prompt or context engineering.
- Solid understanding of AI quality evaluation, benchmarking, observability, regression testing, and monitoring for non-deterministic systems.
- Experience with cloud environments, preferably AWS, along with Kubernetes, containerization, Infrastructure-as-Code tools, CI/CD pipelines, Linux systems, networking fundamentals, and monitoring solutions.
- Excellent communication, leadership, and decision-making skills, with the ability to balance strategic planning, technical execution, and people management.


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Benefits
- Fully remote position with collaboration across the European time zone.
- Opportunity to lead a highly impactful AI product with significant ownership and technical influence.
- Hands-on leadership role combining engineering management with active software development.
- Exposure to cutting-edge AI technologies, including LLMs, inference infrastructure, GPU computing, and distributed systems.
- Close collaboration with cross-functional engineering, infrastructure, product, and security teams.
- Career growth through technical leadership, architecture ownership, and strategic decision-making.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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