Head of AI Engineering

Join to apply for the Head of AI Engineering role at Neurons Lab

Lead our AI engineering team to transfer systems for financial services. You’ll manage a team of AI architects and engineers while automating workflows with AI agents. We’re creating production‑ready AI solutions for banks, insurance companies, and investment firms—from customer support bots to document automation and productivity assistants.

Objective & KPIs
Build a self‑sustaining AI‑native engineering function that delivers high‑quality, compliant, and reusable agentic solutions for FSI clients while maximizing automation and team leverage.

Develop PoCs in 2 weeks; develop production solutions in 2 months

≥ 50 % internal engineering workflows fully automated by autonomous AI agents (baseline FY‑2025 audit)

≥ 75 % code/component reuse across new projects

Production model accuracy ≥ 90 %, latency  Maintain 0.375–0.5 FTE as billable hours allocation at the client’s projects

Areas of Responsibility

Talent & Capability Building

Hire, onboard, and retain A‑player AI Architects and AI engineers

Empower AI architects and engineers with clear decision rights, context, and AI‑native tooling so they can execute autonomously and at speed

Implement a skills‑matrix and personalized growth plans; coach next‑generation tech leads

Make decisions on promotion based on performance reviews anchored in objective contribution metrics

Promote a culture of continuous learning (regular "Agentic AI dojo", conference sponsor ships, internal certifications)

Provide technical oversight through senior AI Architects across all client engagements; sign off on architecture and go‑live readiness while mentoring them to own delivery

Staff projects with the right talent mix; optimize utilization of core team members

Engineering Excellence & AI‑Native 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 AI‑native SDLC: LLM‑assisted coding & test generation, agentic design patterns, self‑healing pipelines, prompt‑ops, red‑teaming, 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 ≥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

Skills

AI‑native software engineering & agentic architectures

MLOps automation and observability

Large‑scale AWS (Sage Maker, Bedrock, EKS) optimisation

Regulatory & security compliance for FSI

Organizational design and talent development

KPI‑driven process improvement

Strategic thinking & systems‑level problem‑solving

Knowledge

Core‑banking, insurance, and asset‑management data flows & systems

LLM orchestration patterns and prompt engineering best practices

Foundations of traditional machine learning and ML models training from scratch

Financial‑services regulatory frameworks

AWS Marketplace packaging and Advanced‑Tier Partner requirements

Code‑quality measurement (e.g., Codacy) and secure SDLC principles

Experience

Led AI/ML engineering teams 15 → 50+ in FSI domain while maintaining velocity; delivered production agentic AI systems with ≥ 90 % accuracy &  Deployed autonomous AI agents that automated ≥ 40 % of engineering/business processes

Established, maintained, and improved engineering standards and quality measures

Seniority level

Director

Employment type

Full‑time

Job function

Engineering and Information Technology

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