Senior Agentic AI / SDLC Engineer

Quick Facts

• Role: Senior Agentic AI / SDLC Engineer (hands-on)
• Project: Agentic SDLC—design, build, and productionize AI-driven solutions across the software delivery lifecycle
• Work model: Hybrid — 1 day/week in Warsaw office, rest remote
• Engagement: Long-term

Description

Design, build, and productionize Agentic SDLC solutions that use AI to transform software engineering—from requirements analysis, development and code review, through testing, CI/CD, and operations. You will create and integrate AI agents, workflows, and developer-tool integrations, then harden, monitor, measure outcomes, and optimize LLM usage costs. Work is conducted hands-on with engineering teams via pair/mob programming, collaborative code reviews, and architecture/design on real use cases.

Responsibilities

• Design, build, and production-deploy AI agents and Agentic SDLC workflows
• Integrate AI solutions with code repositories, developer tools, CI/CD, code review, and testing processes
• Build skills, prompts, and automations supporting SDLC roles
• Use tools such as GitHub Copilot, Claude Code, Cursor, Codex, M365 Copilot, and open-source models
• Design LLM, RAG, and agent-architecture-based solutions
• Productionize AI solutions: configuration, integration, hardening, monitoring, and iterative development
• Lead technical discovery and workshops to identify business and technical needs
• Translate needs into use cases, implementation initiatives, and target solution architecture
• Assess business value, measure implementation results, and optimize LLM model costs
• Introduce and standardize Spec-Driven Development and Agentic SDLC practices
• Tailor AI tools and practices to different roles: Developer, QA, Analyst, DevOps
• Hands-on development with pair/mob programming and shared code reviews
• Transfer knowledge and enable teams to independently maintain and evolve the deployed solutions
• Gradually hand over ownership and responsibilities to the final teams
• Maintain, evolve, and measure the effectiveness of deployed AI solutions

Requirements

• Minimum 5 years of technical experience as a Software Developer, DevOps Engineer, QA/Test Automation Engineer, or comparable software-delivery role
• Strong practical knowledge of the full SDLC and experience in product/delivery engineering teams
• Hands-on experience designing and implementing AI solutions within software development processes
• Experience with AI tools such as GitHub Copilot, Claude Code, Cursor, Codex, M365 Copilot, or open-source models
• Practical ability to create AI Agents, workflows, skills, and advanced prompts
• Experience integrating AI with repositories, CI/CD, code review, and test automation
• Knowledge of Spec-Driven Development and modern AI-assisted engineering practices
• Understanding of LLM, RAG, automation, and agent architecture
• Experience with production deployment of AI solutions (integration, configuration, hardening, monitoring, and ongoing improvement)
• Ability to run technical discovery and translate business/technical needs into architecture and concrete solutions
• Ability to estimate business value, measure outcomes, and optimize LLM usage costs
• Experience with real knowledge transfer: pair/mob programming, code reviews, and joint design/development
• Ability to standardize Agentic SDLC practices and adapt AI use across roles in the team
• Experience or strong familiarity with security and compliance in large financial organizations
• Excellent communication skills with engineers and leadership (managers/directors)
• Independence, analytical mindset, openness to experimentation, and ongoing tracking of AI advances

Benefits

• Long-term collaboration
• Technical training, certifications, and continuous skill growth
• Mentoring Competence Center community from day one (conferences and sharing expertise)
• Clear career path
• Employee benefits package: Multisport, private medical care, life insurance
• Friendly work environment with integration events and team-building activities