Agentic SDLC Engineer

Quick Facts

• Build AI agent–driven software development processes and workflows

Description

You will join a team delivering a strategic AI transformation focused on an Agentic SDLC model. The work covers designing, building, and implementing AI agents, workflows, and integrations with developer environments and CI/CD. You will collaborate with product teams to support business analysis, system design, development, testing, documentation, application maintenance, and backlog management, while shaping the organization’s target operating model for AI in the SDLC.

Responsibilities

• Design, build, and implement AI agents and workflows for SDLC use cases
• Integrate agent solutions with developer tooling and CI/CD processes
• Support end-to-end software lifecycle activities (analysis, design, development, testing, documentation, maintenance)
• Define AI-related operating model elements: governance, standards, metrics, and competence/process expectations
• Drive knowledge transfer and build organizational self-sufficiency after implementation

Requirements

• Minimum 5 years of experience in software development, DevOps, QA/Test Automation, or similar roles
• Experience in development teams and full application lifecycle understanding
• Practical hands-on experience with AI SDLC tools (GitHub Copilot, Cursor, Claude Code, Codex, M365 Copilot)
• Experience building AI agents/workflows/prompts and integrating with developer environments
• Knowledge of LLM, RAG, agent architectures, and process automation
• Production deployment experience for AI solutions
• Ability to run discovery workshops and map business needs to technical solutions
• Ability to evaluate business value and measure AI deployment outcomes
• Strong communication and consulting skills
• Experience with knowledge transfer and collaboration practices (pair programming, code review)
• Familiarity with Spec-Driven Development
• Familiarity with large financial organization realities and security/compliance requirements
• Self-driven, analytical approach and continuous learning mindset

Benefits

• Dynamic working environment and opportunities for growth
• Access to communities and training (Jit Communities, Jit Team events)
• Knowledge transfer and collaborative delivery within a partner model