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Location: 100% Remote – must work EST hours
Engagement Type: Contract (12–24 months)
Job Summary:
We’re seeking an experienced AI Engineering Lead to drive AI adoption and SDLC transformation across our banking client’s Loan Servicing technology organization. This is a hands-on technical leadership role focused on implementing AI tooling, modernizing software delivery, automating documentation, and building an agentic development framework.
You will own the AI strategy for engineering teams, establish governance and best practices, and help accelerate delivery through intelligent automation.
Top Responsibilities:
AI Platform & Governance
- Deploy and manage Microsoft 365 Copilot Chat and Copilot Studio for engineering teams.
- Design and implement AI agents and workflows for code review, documentation, testing, and support.
- Establish AI governance, guardrails, approval workflows, and quality controls.
- Integrate AI capabilities with GitLab, Jira, and test management tools.
SDLC Transformation
- Assess current development processes and implement AI-enabled improvements.
- Streamline requirements, development, testing, and deployment workflows.
- Define metrics and measure improvements in delivery speed, quality, and efficiency.
Reverse Engineering & Documentation
- Analyze existing applications across mainframe and distributed environments.
- Generate and maintain business, architecture, and technical documentation.
- Build traceability from requirements through testing and deployment.
- Create sustainable documentation practices that stay aligned with the codebase.
Agentic Development
- Design and pilot a network of AI agents supporting requirements, development, testing, and code review.
- Define human-in-the-loop controls and approval processes.
- Develop a scalable operating model for broader adoption.
Enablement & Leadership
- Coach teams on AI-assisted development and responsible AI practices.
- Develop reusable prompts, templates, and workflows.
- Serve as the organization’s AI subject matter expert.
Must Have Requirements:
- 10-15+ years of software engineering experience (strong systems-thinking and architecture skills)
- 3+ years in a Lead or Principal Engineer, or similar senior technical role.
- Experience leading a specific AI tooling or SDLC transformation initiative
- Hands-on experience with the agent design, deployment, and governance for Microsoft Copilot Chat and Copilot Studio
- Experience implementing AI agents or agentic frameworks (AutoGen, CrewAI, LangGraph, Semantic Kernel, Duo, etc.).
- Experience with GitLab CI/CD, Jira, and software testing practices.
- Ability to analyze and understand enterprise codebases, including Java
- Experience creating architecture documentation, requirements documentation, and traceability artifacts.
- Soft Skills:
- Ability to work independently in ambiguous environments.
- Excellent communication and stakeholder management abilities.
Nice to Have:
- Banking, financial services, or loan servicing experience
- Mainframe experience (COBOL, JCL, CICS). Familiarity with mainframe modernization patterns and the challenges of wrapping or extending COBOL/CICS assets in hybrid architectures.
- Experience with containerized deployments: Docker and Kubernetes in a CI/CD context.
- Background in prompt engineering, RAG (Retrieval-Augmented Generation), or enterprise LLM integration patterns.
- Microsoft certifications: AI-102 (Azure AI Engineer), MS-900/M365, or Power Platform/CoPilot Studio certifications.
- Exposure to regulatory compliance frameworks relevant to banking (e.g., SOX, FFIEC, OCC guidance on model risk and AI governance).