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AI Engineering Lead

Job in Buffalo, Erie County, New York, 14266, USA
Listing for: Coforge
Full Time position
Listed on 2026-07-22
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, DevOps
Salary/Wage Range or Industry Benchmark: 150000 - 230000 USD Yearly USD 150000.00 230000.00 YEAR
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.
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).
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