AI Engineer
Full Time
On-site
Xoriant Corporation
Fitment
Dice Job Match Score™
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Job Details
Skills
- Orchestration
- Bill Of Materials
- Mechanical Engineering
- Workflow
- Streaming
- Network
- Mapping
- Ontologies
- Python
- Prompt Engineering
- Semantics
- Autogen
- Extraction
- Optical Character Recognition
- PDF
- Layout
- Resource Description Framework
- OWL
- SPARQL
- Microsoft Azure
- Artificial Intelligence
- Microsoft Certified Professional
- Servers
- Energy
- IoT
- SCADA
- MQTT
- Stacks Blockchain
- Evaluation
Summary
Job Requirements
2.1 AI Engineers (2 positions)
The AI engineers will design, build, and iterate on AI agent capabilities within an agentic orchestration framework. Work will span:
Agent orchestration and workflow execution - Implementing multi-step agent pipelines with human-in-the-loop approval gates, state persistence, and resumable execution
Document intelligence - Building extraction and classification capabilities for engineering documents (single-line diagrams, bills of material, mechanical drawings, site profiles, tariff schedules) using LLM-based pipelines
Knowledge graph construction and validation - AI-driven generation, enrichment, and deterministic validation of RDF/OWL knowledge graphs representing physical assets and their relationships
Conversational AI - Extending a chat-based interface that allows operators to query operational data, trigger agent workflows, and review AI-generated recommendations
Device and telemetry classification - Agents that identify and classify new devices and telemetry streams appearing on the network, mapping them to canonical ontology types
Observability and evaluation - Instrumenting agents with structured logging, tracing, and quality scoring to support iterative prompt engineering and reliability improvements
Required skills: - Strong Python development (3+ years production experience) - Hands-on experience building LLM-powered applications (prompt engineering, RAG, tool use / function calling, structured output) - Experience with at least one agent framework (LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent) - Familiarity with document extraction pipelines (OCR, PDF parsing, layout-aware models) - Working knowledge of RDF, OWL, SPARQL, or similar knowledge representation technologies - Experience with Azure AI services (Azure OpenAI, Azure AI Document Intelligence, or Azure AI Foundry)
Preferred skills: - Experience with Model Context Protocol (MCP) tool servers - Background in energy, industrial IoT, or SCADA systems - Familiarity with Sparkplug B or MQTT protocol stacks - Experience with evaluation frameworks for LLM applications (e.g., promptfoo, ragas, or custom harnesses)
2.1 AI Engineers (2 positions)
The AI engineers will design, build, and iterate on AI agent capabilities within an agentic orchestration framework. Work will span:
Agent orchestration and workflow execution - Implementing multi-step agent pipelines with human-in-the-loop approval gates, state persistence, and resumable execution
Document intelligence - Building extraction and classification capabilities for engineering documents (single-line diagrams, bills of material, mechanical drawings, site profiles, tariff schedules) using LLM-based pipelines
Knowledge graph construction and validation - AI-driven generation, enrichment, and deterministic validation of RDF/OWL knowledge graphs representing physical assets and their relationships
Conversational AI - Extending a chat-based interface that allows operators to query operational data, trigger agent workflows, and review AI-generated recommendations
Device and telemetry classification - Agents that identify and classify new devices and telemetry streams appearing on the network, mapping them to canonical ontology types
Observability and evaluation - Instrumenting agents with structured logging, tracing, and quality scoring to support iterative prompt engineering and reliability improvements
Required skills: - Strong Python development (3+ years production experience) - Hands-on experience building LLM-powered applications (prompt engineering, RAG, tool use / function calling, structured output) - Experience with at least one agent framework (LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent) - Familiarity with document extraction pipelines (OCR, PDF parsing, layout-aware models) - Working knowledge of RDF, OWL, SPARQL, or similar knowledge representation technologies - Experience with Azure AI services (Azure OpenAI, Azure AI Document Intelligence, or Azure AI Foundry)
Preferred skills: - Experience with Model Context Protocol (MCP) tool servers - Background in energy, industrial IoT, or SCADA systems - Familiarity with Sparkplug B or MQTT protocol stacks - Experience with evaluation frameworks for LLM applications (e.g., promptfoo, ragas, or custom harnesses)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: xorca001
- Position Id: XAAXAAGBP100923EXTERNALENIN
- Posted 1 day ago
Company Info
Xoriant is a Sunnyvale, CA headquartered digital engineering firm with offices in the USA, Europe, and Asia. From Tech Startups to Fortune 100 Enterprises, we enable innovation, accelerate time to market, and ensure client competitiveness across industries. Across all our focus areas – platform engineering, cloud, data & and AI, and Security – every solution we develop benefits from our product engineering DNA and culture of innovation. It also includes successful methodologies, framework components, and accelerators for rapidly solving critical client challenges. For 30 years and counting, we have taken great pride in the longlasting, deep relationships we have with our clients.
For further information about Xoriant, please visit our website
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