AI-Native Software Engineering; reinvent E2E PDLC, SDLC; AI mentoring the team

Project overview

A leading consulting company is looking for a Senior AI-Native Engineering / Software Lead. This role involves supporting the end-client in the banking sector. This role is based in Zürich, Switzerland.

The ideal candidate combines a solid software engineering background with extensive hands-on experience using AI-powered development tools, coding agents, and agentic workflows.

The primary mission of this engagement is not to develop standalone AI applications, chatbots, or machine learning models. Instead, the goal is to fundamentally redesign and elevate the entire Product Development Lifecycle (PDLC) and Software Development Lifecycle (SDLC) through the practical adoption of AI-powered development tools, coding agents, and agentic workflows.

Skills Must - Haves

Skills Nice-to-HavesIdentity & Access Management (IAM): Familiarity with core identity and access protocols (e.g., OAuth 2.0, OpenID Connect, SAML) or hands-on experience navigating large-scale enterprise platform migration programmes.

The Don'ts

To ensure clear alignment on the nature of this hands-on engineering transformation role, we are not looking for:

• Extensive Software Engineering Foundation: Proven track record in professional software engineering, with deep experience designing, developing, testing, and maintaining mission-critical enterprise applications.
• Practical LLM & Agentic Workflows: Deep, hands-on engineering experience working with Large Language Models (LLMs) and Generative AI, including retrieval-augmented generation (RAG), structured data extraction, tool/function calling, and multi-step agentic workflows.
• AI-Native Development Tooling: Extensive, day-to-day practical experience leveraging modern AI developer tools (preferably GitHub Copilot) and autonomous coding agents embedded into your active development cycle.
• AI Automation at Scale: Demonstrable success deploying AI-powered automations, agents, or workflows directly within existing large-scale, complex enterprise codebases and architectures—moving beyond standalone scripts or isolated proof-of-concepts.
• Comprehensive PDLC / SDLC Mastery: Thorough understanding of all stages of product and software delivery (requirements breakdown, system architecture, development, automated testing, CI/CD, deployment, and ongoing maintenance).
• DevOps & Platform Engineering Collaboration: Hands-on automation and DevOps experience, paired with the ability to collaborate directly with platform and infrastructure engineers.
• Rapid Prototyping & Pragmatic Execution: A bias for action, capable of taking ambiguous problem statements, rapidly building working prototypes/proofs-of-concept, and iterating closely alongside users and teams.
• Team Enablement & Mentorship: Demonstrated capability to coach developers, challenge established engineering mindsets, and guide teams through adopting new AI-first methodologies.
• Consulting & Stakeholder Communication: Strong interpersonal and consulting skills, capable of establishing technical credibility with engineers while communicating strategy effectively to stakeholders.
• Adaptability: High resilience and flexibility to adjust priorities and approaches within a fast-moving enterprise setting.
• Configuration Transformation: Experience parsing, comparing, analyzing, and programmatically transforming large volumes of application configuration data.
• AI Governance & Guardrails: Experience designing and implementing automated guardrails, evaluation frameworks, human approval gates, and traceability standards for AI-generated code and systems.
• Workshops & Technical Training: Background in structuring and leading interactive training workshops, technical masterclasses, or enablement bootcamps for engineering teams.
• A Data Scientist or Machine Learning Researcher: This engagement does not involve training models, fine-tuning neural networks, or standard data science workflows.
• A Dedicated AI Application/Chatbot Builder: We are not hiring to build customer-facing conversational interfaces, standalone chatbot products, or consumer RAG applications.
• A Purely Conceptual Enterprise Architect: We require an active practitioner who writes code, builds agents, and works in the repository alongside engineers, not an advisor focused solely on high-level target architectures and slide decks.
• A Transformation Consultant Without Deep Engineering Depth: Process and change management skills are vital, but only when anchored in substantial, current hands-on software development experience.
• A Traditional Developer with Casual AI Exposure: The position requires an engineer who has deeply integrated AI coding agents into their daily development habits, rather than someone who only occasionally uses autocomplete assistants.

Project details

• Start: 2026-11
• Duration: 2 Monate
• Remote: hybrid
• Location: Zürich, Schweiz, CH