DeepRec.ai
Technical Lead / Solutions Architect, Applied AI

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An AI company delivering end-to-end AI solutions—spanning foundation models, developer tooling, and enterprise-grade applications—is hiring a Technical Lead for its Applied AI function.
This person will oversee delivery of advanced AI systems for large customers operating in regulated or high-complexity sectors such as banking, healthcare, and industrial production.
What This Role Involves
This is a player-coach position: you'll manage a small team of AI engineers while staying directly involved in building and reviewing code for the most technically demanding pieces of each engagement. You'll be the go-to technical contact for key accounts, spanning early scoping conversations through to rollout and support, and you'll coordinate closely with teams in research, product, and engineering.
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.
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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.
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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.
Core Responsibilities
- Contribute directly as an engineer on high-stakes workstreams (model fine-tuning, retrieval-augmented generation, multi-step agent systems, bespoke LLM builds)
- Guide and coach a group of applied engineers, establishing technical direction and quality bars
- Support pre-sales by turning client requirements into workable technical proposals
- Track new developments in the field and bring promising approaches into the team's toolkit
- Loop customer learnings back to product and engineering to shape what gets built next
Candidate Profile
- Strong written and spoken English
- Master's or doctoral degree in machine learning, computer science, or an adjacent discipline
- 7+ years working in AI/ML, with 2+ years spent in a lead capacity (e.g., Engineering Manager, Tech Lead, Solutions Architect)
- History of shipping AI systems end-to-end, from early prototype to live production use
- Solid grounding in fine-tuning approaches, sophisticated RAG pipelines, and agent-based architectures at scale
- Hands-on coding ability in Python and PyTorch, plus familiarity with common ML tooling
- Background in backend or full-stack engineering, including API and systems design
- Comfortable presenting technical material to both engineers and non-technical leadership


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Also Valuable
- Involvement in open-source AI/ML projects
- Previous work in a client-facing capacity (e.g., Solutions Engineer, Technical Account Manager)
- Experience shaping a product roadmap using direct customer input
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