AIML Architect
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Job Location:
Monthly Salary:
Posted on:
5 days ago
Vacancies:
1 Vacancy
Job Summary
Key Responsibilities
Lead end-to-end architecture of AI/ML and GenAI solutions across FEED EPC
and operations-support phases.
Architect enterprise grade Retrieval-Augmented Generation (RAG) systems
leveraging vector databases embedding models chunking strategies and
semantic pipelines for EPC knowledge search.
Design and implement cognitive search and next generation enterprise search
platforms using Azure Cognitive Search ML embeddings and multimodal
retrieval.
Define and operationalize LLM Ops / MLOps frameworks including CI/CD for
models evaluation pipelines model monitoring prompt management and
guardrails.
Implement LLM judges synthetic evaluation workflows and automated quality
scoring to ensure responsible reliable AI outputs.
Develop architecture patterns for Azure AI Foundry Azure ML Prompt Flow
Azure OpenAI and cloud native deployment pipelines.
Lead technical design of data ingestion enrichment feature stores and
distributed model training (e.g. Spark Databricks).
Ensure alignment with enterprise data cataloging and governance tools such as
Purview and Collibra.
Lead end-to-end architecture of AI/ML and GenAI solutions across FEED EPC
and operations-support phases.
Architect enterprise grade Retrieval-Augmented Generation (RAG) systems
leveraging vector databases embedding models chunking strategies and
semantic pipelines for EPC knowledge search.
Design and implement cognitive search and next generation enterprise search
platforms using Azure Cognitive Search ML embeddings and multimodal
retrieval.
Define and operationalize LLM Ops / MLOps frameworks including CI/CD for
models evaluation pipelines model monitoring prompt management and
guardrails.
Implement LLM judges synthetic evaluation workflows and automated quality
scoring to ensure responsible reliable AI outputs.
Develop architecture patterns for Azure AI Foundry Azure ML Prompt Flow
Azure OpenAI and cloud native deployment pipelines.
Lead technical design of data ingestion enrichment feature stores and
distributed model training (e.g. Spark Databricks).
Ensure alignment with enterprise data cataloging and governance tools such as
Purview and Collibra.
Collaborate with engineering and project execution functions to identify
EPC/EPCM specific AI use cases (schedule intelligence quantity forecasting
construction quality insights materials optimization and risk prediction).
Support evaluation and integration of commercial tools GenAI copilots and
advanced engineering data systems.
Produce architecture documents reference patterns solution blueprints and
technical roadmaps for internal and client-facing reviews.
Mentor data scientists ML engineers and developers on best practices in AI
architecture cloud engineering and LLM-driven workflow design.
EPC/EPCM specific AI use cases (schedule intelligence quantity forecasting
construction quality insights materials optimization and risk prediction).
Support evaluation and integration of commercial tools GenAI copilots and
advanced engineering data systems.
Produce architecture documents reference patterns solution blueprints and
technical roadmaps for internal and client-facing reviews.
Mentor data scientists ML engineers and developers on best practices in AI
architecture cloud engineering and LLM-driven workflow design.
Required Qualifications
10 years of experience in AI/ML data engineering or solution architecture
roles.
Hands-on experience architecting and deploying AI/ML or GenAI solutions at
enterprise scale.
Strong proficiency in Python ML frameworks (PyTorch TensorFlow Scikitlearn)
and distributed compute (Spark).
Expertise with Azure AI ecosystem (Azure ML Azure AI Foundry Azure OpenAI
Databricks ADF Synapse).
Experience designing RAG architectures vector stores (Milvus FAISS Qdrant
Chroma Azure AI Search vector index) and embedding model pipelines.
Deep understanding of MLOps / LLM Ops including model registries monitoring
orchestration and evaluation.
Strong understanding of cloud security identity data governance and
compliance.
Ability to translate complex requirements into long-term scalable AI architectures.
Experience with Azure Cognitive Search (index design enrichment pipelines
semantic hybrid retrieval).
Hands-on experience deploying or fine-tuning selfhosted LLMs in onprem or
VNet-isolated environments using GPU clusters.
Strong understanding of vector databases (Pinecone Weaviate Milvus Chroma
pgvector).
10 years of experience in AI/ML data engineering or solution architecture
roles.
Hands-on experience architecting and deploying AI/ML or GenAI solutions at
enterprise scale.
Strong proficiency in Python ML frameworks (PyTorch TensorFlow Scikitlearn)
and distributed compute (Spark).
Expertise with Azure AI ecosystem (Azure ML Azure AI Foundry Azure OpenAI
Databricks ADF Synapse).
Experience designing RAG architectures vector stores (Milvus FAISS Qdrant
Chroma Azure AI Search vector index) and embedding model pipelines.
Deep understanding of MLOps / LLM Ops including model registries monitoring
orchestration and evaluation.
Strong understanding of cloud security identity data governance and
compliance.
Ability to translate complex requirements into long-term scalable AI architectures.
Experience with Azure Cognitive Search (index design enrichment pipelines
semantic hybrid retrieval).
Hands-on experience deploying or fine-tuning selfhosted LLMs in onprem or
VNet-isolated environments using GPU clusters.
Strong understanding of vector databases (Pinecone Weaviate Milvus Chroma
pgvector).
Expertise in Responsible AI model governance jailbreak testing and prompt-
injection defense.
Experience optimizing LLM performance using quantization ONNX Runtime
TensorRT DeepSpeed.
injection defense.
Experience optimizing LLM performance using quantization ONNX Runtime
TensorRT DeepSpeed.
Preferred Qualifications
EPC/EPCM project experience in energy chemicals mining infrastructure
ATLS or data centers.
Experience with engineering data ecosystems (Hexagon SmartPlant Aveva
BIM/Digital Twin systems).
Knowledge of Azure Prompt Flow Function Calling agents/orchestration
frameworks and safety/guardrail patterns.
Familiarity with Purview Collibra and metadata-driven governance.
Certifications such as Azure Solutions Architect Expert Azure Data Engineer or
Databricks Architect.
Experience with agentic frameworks (Semantic Kernel AutoGen CrewAI
LangGraph).
Familiarity with LLM observability (App Insights Prometheus OpenTelemetry).
Experience with enterprise indexing metadata extraction and enrichment
platforms.
Knowledge of secure multi-tenant AI architecture for large engineering
organizations.
Expertise with API gateways service mesh and event-driven architectures
(Kafka/Event Hub).
EPC/EPCM project experience in energy chemicals mining infrastructure
ATLS or data centers.
Experience with engineering data ecosystems (Hexagon SmartPlant Aveva
BIM/Digital Twin systems).
Knowledge of Azure Prompt Flow Function Calling agents/orchestration
frameworks and safety/guardrail patterns.
Familiarity with Purview Collibra and metadata-driven governance.
Certifications such as Azure Solutions Architect Expert Azure Data Engineer or
Databricks Architect.
Experience with agentic frameworks (Semantic Kernel AutoGen CrewAI
LangGraph).
Familiarity with LLM observability (App Insights Prometheus OpenTelemetry).
Experience with enterprise indexing metadata extraction and enrichment
platforms.
Knowledge of secure multi-tenant AI architecture for large engineering
organizations.
Expertise with API gateways service mesh and event-driven architectures
(Kafka/Event Hub).
Skills & Competencies
AI/ML Architecture
LLM & GenAI Engineering
RAG Pipeline Design
Vector Databases & Semantic Search
AI/ML Architecture
LLM & GenAI Engineering
RAG Pipeline Design
Vector Databases & Semantic Search
Cognitive Search & Document Intelligence
MLOps / LLM Ops
Python & Distributed Computing
Cloud Architecture (Azure)
Data Governance & Lineage
Technical Leadership & Collaboration
Excellent communication and stakeholder engagement
MLOps / LLM Ops
Python & Distributed Computing
Cloud Architecture (Azure)
Data Governance & Lineage
Technical Leadership & Collaboration
Excellent communication and stakeholder engagement
