Description :

Qualifications :

- 4+ years of professional software engineering experience, with at least 23 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 coordination

Deep familiarity with context & retrieval design, including :

- RAG pipelines and embedding strategies

- Retrieval quality evaluation

- Grounding and prompt-context isolation

- Vector stores & document indexing

Strong 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

- Act as a technical leader and architectural partner across accelerator initiatives.

- Coach junior engineers through pairing, reviews, and design walkthroughs.

- Advocate for reusable patterns and forward-compatible designs.

- Contribute to a culture of experimentation, evidence-based iteration, and shared learning.