Senior AI Engineer

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.
  

Requirements

Qualifications:

• 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 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.
  

Signs You May Be a Great Fit

• Impact: Play a pivotal role in shaping a rapidly growing venture studio.
  

• Culture: Thrive in a collaborative, innovative environment that values creativity and ownership.
  

• Growth: Access professional development opportunities and mentorship.
  

• Benefits: Competitive salary, health/wellness packages, and flexible work options.