Technical Lead / Solutions Architect, Applied AI

Technical Lead / Solutions Architect, Applied AI

Full-Time 70000 - 90000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead a team in delivering advanced AI solutions while coding and reviewing high-stakes projects.
  • Company: Innovative AI company focused on end-to-end solutions for complex industries.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic role with opportunities to influence product development and client engagement.
  • Why this job: Make a real impact in AI while mentoring a talented team and shaping future technologies.
  • Qualifications: Master's or doctoral degree in relevant fields and extensive experience in AI/ML leadership.

The predicted salary is between 70000 - 90000 £ per year.

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.

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

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

Technical Lead / Solutions Architect, Applied AI employer: DeepRec.ai

At DeepRec.ai, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Greater London. Our commitment to employee growth is evident through our focus on cutting-edge AI technologies and the opportunity to lead transformative projects that have a real impact on the future of science. With competitive compensation, a supportive environment, and the chance to work alongside industry leaders, we provide a unique platform for engineers passionate about making a difference in the world of AI.

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Contact Details:

DeepRec.ai Recruitment Team

We think you need these skills to ace Technical Lead / Solutions Architect, Applied AI

Machine Learning
Python
PyTorch
AI Systems Development
Model Fine-Tuning
Retrieval-Augmented Generation (RAG)
Agent-Based Architectures