Agentic SDLC Transformation Lead — Talan

Full description

Context & Challenges

You are steering the transformation of the software development life cycle (SDLC) toward an industrial model augmented by Artificial Intelligence (AI-Driven / Agentic SDLC).

Your role is to orchestrate and embed over time a transformation of engineering practices. The objective: to structure a modern methodological framework in which developers and AI agents collaborate smoothly, securely and under governance, in order to accelerate delivery speed while raising software quality standards.

Positioned as a true Tech Transformation & Change Leader, you bridge the gap between strategic vision, team enablement and concrete technical implementation in the field (hands-on).

Main Responsibilities

Structuring the Methodological Framework (AI-SDLC)

• Define and deploy the augmented engineering framework covering the entire life cycle:
• Automated exploration and mapping of the existing application landscape.
• Formalization of AI-driven specifications (Specification-Driven Development).
• Architecture design and development guided by specialized agents.
• Advanced automation of validation, acceptance testing and quality control.
• Dynamic documentation and knowledge management (Knowledge Management).
• Establish standards and governance rules to guarantee the traceability, repeatability, security and scalability of deliverables.

Architecture & Agent Orchestration

• Model an ecosystem of autonomous and collaborative virtual agents tailored to the challenges faced by development teams.
• Structure the roles, contexts and knowledge bases handled by agents at each stage of the cycle.
• Implement orchestration mechanisms, human-in-the-loop control loops and inter-stage handoffs (handoffs).
• Establish financial oversight of model consumption and token management (TokenOps).

Change Management & Adoption at Scale

• Embody the CTO role to educate, convince and unite engineering teams around new practices.
• Design demonstrators, POCs and high-impact use cases to prove value in the field.
• Deploy the framework with pilot teams, then structure its rollout at scale (creation of a foundation of reusable components, templates, reference repositories).
• Identify and remove organizational, technical or cultural barriers to AI adoption.

Career Path & Experience

• 10+ years of overall experience in software engineering, systems architecture or technical leadership (SVP/VP Engineering, CTO organization, Head of Tech).
• Proven experience leading large-scale engineering transformations (deployment of DevOps, Platform Engineering or scaled Agile practices).
• Practical experience ( Hands-on ) and mastery of Generative AI technologies applied to software development.

Key Technical Skills

• Architecture & Engineering: Software architecture, SDLC, DevOps, CI/CD, test automation.
• Generative AI & Agents: LLMs (integration, limitations), multi-agent systems / autonomous agents, RAG ( Retrieval-Augmented Generation ), Prompt Engineering , Context Engineering .
• Tech Governance: TokenOps, AI FinOps, quality and security of generated code.

Soft Points & Leader

• CTO Stance & Strategic Vision: Ability to challenge the status quo, structure a technical vision and translate it into operational terms.
• Leadership & Change Management: Excellent communicator, capable of bringing senior developers and decision-makers on board, facilitating communities and removing adoption barriers.
• Innovation Mindset & Pragmatism: Results-oriented, with a strong desire to turn prototypes into repeatable, industrialized capabilities.