Agentic SDLC Senior Engineer

Quick Facts

• Role: Agentic SDLC Senior Engineer

Description

You will help design, verify, and implement a target IT operating model for software delivery that uses AI and Agentic SDLC practices as an integral part of the development process. The model will define processes, roles, competencies, governance, metrics, work standards, tool model, AI agent usage rules, and mechanisms for continuous improvement.

Responsibilities

• Lead end-to-end Agentic SDLC rollouts: discovery of needs, pilots, tool configuration, standardization, governance, and scaling.

• Collaborate with managers and leadership to collect requirements, set priorities, and build an AI adoption roadmap.

• Conduct trainings, workshops, consultations, and hands-on sessions for cross-functional engineering teams.

• Support teams in effective use of AI coding tools (e.g., GitHub Copilot, Claude Code, Cursor, Codex, M365 Copilot).

• Design and implement workflows, agents, prompts, skills, and Spec-Driven Development practices supporting analysis, development, testing, code review, documentation, and maintenance.

• Build internal knowledge base, standards, usage patterns, and AI best practices for SDLC.

• Manage resistance to change by communicating benefits, addressing concerns, engaging technical leaders, and supporting teams in changing how they work.

• Define and monitor KPI/OKR and ROI for AI implementations (productivity, quality, delivery time, unit cost of change, and tool adoption).

• Evaluate and recommend AI SDLC solutions considering quality, cost, security, regulatory risks, and organizational compliance policies.

• Create and enforce safe, responsible AI usage rules (data protection, access controls, risk management).

• Monitor AI market developments and translate new opportunities into use cases in the property insurance domain.

Requirements

• Minimum 5 years of experience in a technical role (Software Developer, DevOps Engineer, QA/Test Automation Engineer or similar).

• Practical experience in software delivery teams and knowledge of the full application lifecycle.

• Hands-on experience designing and implementing AI-based solutions in SDLC (e.g., GitHub Copilot, Claude Code, Cursor, Codex, M365 Copilot, open-source models).

• Ability to build AI agents, workflows, skills, and prompts and integrate them into engineering environments (repositories, CI/CD, code review, testing).

• Knowledge of Spec-Driven Development and modern AI-supported software engineering practices.

• Understanding of LLM concepts, RAG, automation, and agent architectures; experience with frameworks such as LangGraph is a plus, and knowledge of MCP is a plus.

• Production experience deploying AI solutions (configuration, integration with organizational systems, hardening, monitoring, iterative development).

• Ability to translate business and technical requirements into concrete implementation initiatives and solution architecture, including using technical workshops for discovery.

• Ability to assess the business value of AI, optimize model usage costs, and measure deployment outcomes.

• Strong communication and consulting skills; able to conduct discussions with technical teams, managers, and directors.

• Experience transferring engineering knowledge during delivery (pair/mob programming, shared code review, joint design and build on real tasks).

• Ability to standardize AI tool practices within the team and select Agentic SDLC practices appropriate for each role (developer, tester, analyst, DevOps).

• Experience supporting production handover to engineering teams: gradual transfer of responsibility, technical sessions during deployments, working side-by-side.

• Familiarity with software delivery realities in a large financial organization and awareness of security and compliance requirements.

• Analytical approach, independence, openness to experimentation, and continuous learning.

Benefits

• Support for professional and personal development.

• Individual support from a Service Delivery Manager to plan your career path and ensure comfort and satisfaction.

• Training, certifications, and conferences—co-funded or fully covered for technical skill development.

• #SmartChange initiative to switch the project based on your preferences.

• Work-life balance support with integrations, sports activities, and inspiring #edge1talks webinars.

• Physical activity support (sports initiatives and gym room rentals).

• Health package: private care, sports card, insurance, and psychological support.

• Flexible benefits: choose how to allocate points in the benefits system.

• Hybrid work model: 1 day per week in the Warsaw office and 4 days remote.