Head of Engineering
Neurons Lab
- Roma
- Tempo indeterminato
- Full time
- Mean leadâtime from prototype commit to production †5 days.
- â„ 50 % internal engineering workflows fully automated by autonomous AI agents (baseline FYâ2025 audit).
- â„ 75 % code/component reuse across new projects.
- Talent & Capability Building
- Hire, onboard, and retain Aâplayer AI Architects and AI engineers
- Empower AI architects and engineers with clear decision rights, context, and AIânative tooling so they can execute autonomously and at speed.
- Implement a skillsâmatrix and personalised growth plans; coach nextâgeneration tech leads.
- Make decisions on promotion based on performance reviews anchored in objective contribution metrics.
- Promote a culture of continuous learning (regular âAgentic AI dojoâ, conference sponsorships, internal certifications).
- Provide technical oversight through senior AI Architects across all client engagements; sign off on architecture and goâlive readiness while mentoring them to own delivery.
- Staff projects with the right talent mix; optimise utilisation of core team members
- Engineering Excellence & AIâNative Quality
- Update, automate, and collect AI engineering health indicators - including solution accuracy, latency, model drift, cost efficiency, and code quality - via a fully instrumented MLOps telemetry stack (CI/CD, feature store, observability, drift alerts).
- Establish and iterate the AIânative SDLC: LLMâassisted coding & test generation, agentic design patterns, selfâhealing pipelines, promptâops, redâteaming, security & compliance
- Orchestrate autonomous AI agents to automate internal engineering and business routines such as environment provisioning, compliance evidence capture, cost optimisation, and status reporting.
- Maintain reference architectures and reusable component libraries; achieve â„75% code reuse across all new work.
- Convert learnings from services projects into IP that reduces future build effort by > 40 %.
- Own the design, packaging, and optimisation of Neurons Lab solutions
- AIânative software engineering & agentic architectures
- MLOps automation and observability
- Largeâscale AWS (SageMaker, Bedrock, EKS) optimisation
- Regulatory & security compliance for FSI
- Organisational design and talent development
- KPIâdriven process improvement
- Strategic thinking & systemsâlevel problemâsolving
- Coreâbanking, insurance, and assetâmanagement data flows & systems
- LLM orchestration patterns and prompt engineering best practices
- Foundations of traditional machine learning and ML models training from scratch
- Financialâservices regulatory frameworks
- AWS Marketplace packaging and AdvancedâTier Partner requirements
- Codeâquality measurement (e.g., Codacy) and secure SDLC principles
- Led AI/ML engineering teams 15 â 50 + in FSI domain while maintaining velocity
- Established, maintained and improved engineering standards and quality measures