At a Glance
- Tasks: Lead AI engineering projects, mentor teams, and ensure systems are production-ready.
- Company: Join a leading tech firm with a focus on innovation and collaboration.
- Benefits: Enjoy a competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic role with travel opportunities and a chance to influence industry standards.
- Why this job: Shape the future of AI while working on impactful projects and mentoring the next generation.
- Qualifications: Experience in software engineering, applied AI, and cloud architecture is essential.
The predicted salary is between 60000 - 80000 £ per year.
Location: London (Hybrid with client‑site travel; primary location only)
Contract: Permanent, full‑time
Role Purpose
Lead technical delivery across solution threads: set technical direction, mentor engineers, and ensure systems are production‑ready (reliability, observability, security, runbooks). Continue development through the Applied AI Engineering Academy focused on advanced patterns and engineering leadership.
Responsibilities
- Shape engineering approaches; engage senior stakeholders; articulate trade‑offs; ensure engineering quality across squads and complex client environments.
- Architect enterprise‑grade AI services (agents, RAG pipelines, orchestration layers, platform components); ensure operational readiness; drive Responsible AI, evaluation and best practices.
- Mentor engineers; lead technical reviews; establish reference architectures and reusable accelerators; contribute to internal knowledge sharing and external thought leadership.
Qualifications
- Deep software/systems engineering (Python/TypeScript, distributed systems, CI/CD).
- Applied‑AI expertise: LLM/RAG engineering; evaluation; telemetry/drift monitoring; versioning and release management.
- Cloud architecture (Azure/AWS/GCP), Kubernetes/Docker, serverless, IAM and network security.
- Data engineering depth (Spark/Databricks; ETL/ELT); cloud‑native data + AI architectures.
- Enterprise integration and SRE principles (SLIs/SLOs, runbooks, rollback).
- Consulting leadership: stakeholder, budget and risk management; team leadership.
Nice to have
- Graph/big‑data stacks; streaming; cloud architect certifications and Responsible AI governance credentials.
Travel & working model
Hybrid with periodic client travel across the UK (and occasional international travel).
Legal
EY is an equal opportunity employer. A PhD in Computer Science, Applied Mathematics, or Computer Engineering is desirable but not essential.
Senior/Lead Applied AI Engineer in London employer: hackajob
As a Senior Applied AI Engineer at our London office, you will thrive in a dynamic and inclusive work culture that prioritises innovation and collaboration. We offer robust professional development through our Applied AI Engineering Academy, ensuring you have the tools and mentorship needed to excel in your career. With a hybrid working model and opportunities for client engagement across the UK, you will enjoy a fulfilling work-life balance while contributing to cutting-edge AI solutions.
