AI Systems & Workflow Automation Engineer

Role Overview & Systems Context

Bridge machine intelligence with production software engineering by building deterministic agent workflows, schema validation pipelines, and semantic search systems.

Key Responsibilities

• Implement supervisory multi-agent execution graphs with deterministic failure fallbacks.
• Deploy memory-mapped vector search indexing algorithms and hybrid retrieval pipelines.
• Integrate structured LLM tool-calling endpoints with enterprise ERP and CRM systems.

Technical Competencies & Requirements

• Strong engineering background in modern Python and PHP/Laravel architectures.
• Practical experience deploying production LLM workflows (LangChain, LangGraph, DSPy, or custom orchestrators).
• Familiarity with vector embeddings, indexing structures, and similarity evaluation.

Work Environment & Provisions

• Direct involvement in cutting-edge Urjasoft Labs experiments.
• Dedicated hardware and API compute budgets.
• Full remote work support.