Job Title

We are seeking a Senior AI Engineer to lead the design and development of AI-powered accelerators that streamline and automate complex business workflows, with a strong focus on data-migration programs.This role centers on building reliable, production-grade agentic systems and orchestration frameworks that improve speed, quality and reusability across migration and modernization initiatives. The ideal candidate combines strong hands-on engineering capability with architectural leadership and a passion for enabling teams through shared accelerators, assets, and patterns.Roles & Responsibilities:- Design, build and maintain AI accelerators that enhance productivity and reduce delivery effort across data-migration workflows. - Develop agentic and workflow-automation solutions (multi-agent orchestration, task routing, tool-use pipelines, etc.). - Implement robust context-management strategies (retrieval pipelines, memory stores, episodic context, session-state control). - Architect reliable production systems including evaluation, telemetry, failure-handling, and safety/guardrail patterns. - Partner with engineering and delivery teams to adapt accelerators to live projects and real-world migration scenarios. - Provide architectural guidance, mentorship, and code reviews for junior and mid-level engineers working on related accelerators. - Establish development standards, reusable frameworks, and reference implementations to support scale and reuse. - Collaborate with product and delivery stakeholders to translate business workflows into automatable system designs. - Contribute to documentation, training materials, and onboarding guidance for accelerator adoption across teams.RequirementsQualifications:4+ years of professional software engineering experience, with at least 2–3 years in applied AI / LLM systems.Experience working in consulting, platform engineering, or accelerator-style reusable asset development.Prior involvement in data-migration, modernization, or analytics engineering programs is a strong plus.Strong expertise in LLM-based application development (frameworks such as LangChain, LangGraph, Semantic Kernel, custom orchestration).Proven experience with agentic design patterns, including:- Multi-step task planning & decomposition - Tool-calling / API-driven agents - Workflow graphs & supervisory agents - Long-running task coordinationDeep familiarity with context & retrieval design, including:- RAG pipelines and embedding strategies - Retrieval quality evaluation - Grounding and prompt-context isolation - Vector stores & document indexingStrong software engineering fundamentals:- Python (primary) — testing, packaging, dependency management - Architectural design & code quality best-practices - CI/CD and deployment patterns - Experience designing observability and evaluation loops for AI workflows (telemetry, metrics, regression testing, drift tracking).Experience integrating LLM systems with:- Data platforms / warehouses - Metadata systems and workflow tools - REST / Microservices architectures