AI Engineering Lead
Job in
Buffalo, Erie County, New York, 14266, USA
Listed on 2026-07-22
Listing for:
Coforge
Full Time
position Listed on 2026-07-22
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Software Architect, DevOps
Job Description & How to Apply Below
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., Auto Gen, CrewAI, Lang Graph, 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 Git Lab 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.
- 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.
- 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).
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