AI Engineering Lead

Job Title - AI Engineering Lead

Skills – AI, Agentic AI

Experience – 9-12 years

Location - Buffalo, New York

We at Coforge are hiring an AI Engineering Lead with below skillset;

• 10+ years of software engineering experience, including production ownership of complex, multi-tier applications.
• 3+ years in a Lead Engineer or equivalent senior technical leadership role (individual contributor track).
• Proven hands-on experience with Microsoft 365 CoPilot Chat and CoPilot Studio, including agent design, deployment, and governance.
• Demonstrated experience with the Duo Agentic Platform or comparable agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph, or Microsoft Semantic Kernel).
• Ability to read, analyze, and reverse-engineer source code in at least one of: COBOL/JCL/CICS, Java, or equivalent enterprise language.
• Hands-on experience producing formal software artifacts: BRDs, sequence diagrams, architecture documentation, and requirements-to-test traceability matrices.
• Working knowledge of GitLab CI/CD pipeline configuration, Jira project management, and Zephyr or equivalent test management tooling.
• Strong understanding of software testing disciplines: unit, integration, regression, and test automation frameworks.

Skills & Mindset

• Systems thinker who can map complex legacy architectures and translate them into structured, AI-consumable documentation.
• Comfort operating in ambiguity — you define the approach; you don’t wait for one.
• Strong written and verbal communication skills; able to present technical roadmaps and AI strategies to non-technical stakeholders.
• Disciplined about guardrails, auditability, and responsible AI — especially in a regulated banking environment.

PREFERRED QUALIFICATIONS

• Experience in a banking, financial services, or loan servicing technology environment.
• 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).