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Job DescriptionJob Description
Job Title: Solution Architect
Location:
Remote Employment Type:
Contract About the Role We are seeking a seasoned
Solution Architect
with expertise in
data platforms, cloud architecture, and Generative AI (GenAI) . The ideal candidate will have a strong background in
Databricks
and modern data platforms, while also bringing hands-on experience with
LLMs, Hugging Face, LangChain, and vector databases . You will collaborate with cross-functional teams to define technical roadmaps, architect high-performing
data + AI solutions , and drive innovation across analytics and enterprise AI platforms. Key Responsibilities Architect and lead implementation of
cloud- data and AI platforms
leveraging Databricks, Delta Lake, and MLflow.
Design
GenAI-powered solutions
using LLM frameworks (Hugging Face, LangChain) and
vector databases
(Pinecone, FAISS, Weaviate, Milvus).
Define architecture for
Retrieval-Augmented (RAG)
pipelines and enterprise-scale chatbot/AI assistant solutions.
Collaborate with data engineers, data scientists, and product stakeholders to transform business requirements into
AI-driven technical solutions .
Integrate Databricks notebooks, Apache Spark, and cloud- services (AWS Glue, Azure Data Factory) for batch and real-time data processing.
Implement
governance and security frameworks
using Unity Catalog, IAM, encryption, and compliance controls.
Define
integration patterns
using APIs, event-driven messaging (Kafka/Pub/Sub), and distributed system design.
Participate in
architectural reviews, performance tuning, and cost optimization
across distributed compute frameworks.
Stay updated on
emerging GenAI, data engineering, and MLOps technologies .
Required Qualifications Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
10+ years of experience
in enterprise software, data architecture, or AI solution design.
Strong hands-on expertise with
Databricks (Delta Lake, MLflow, Spark, Unity Catalog) .
Proficiency in at least one cloud platform (AWS, Azure, or GCP), with services like S3, ADLS, BigQuery, or Redshift.
Experience building
LLM and GenAI applications
(chatbots, assistants, RAG pipelines).
Familiarity with
Hugging Face, LangChain, and vector databases
(Pinecone, FAISS, Weaviate, Milvus, Chroma).
Experience with streaming platforms (Kafka, Kinesis, Azure Event Hubs).
Strong knowledge of
data modeling, governance, and orchestration tools
(Airflow, dbt, Prefect).
Excellent communication skills for stakeholder management and solution evangelism.
Skills Certifications in
Databricks, AWS/Azure/GCP Solution Architecture, or TOGAF .
Knowledge of
model lifecycle management, versioning, and MLOps practices .
Familiarity with
Generative AI APIs
(OpenAI, Anthropic Claude, Cohere).
Experience with
Unity Catalog, Great Expectations, or other data quality frameworks .
Background in
regulated industries
(finance, healthcare, insurance).
#J-18808-Ljbffr
Remote Employment Type:
Contract About the Role We are seeking a seasoned
Solution Architect
with expertise in
data platforms, cloud architecture, and Generative AI (GenAI) . The ideal candidate will have a strong background in
Databricks
and modern data platforms, while also bringing hands-on experience with
LLMs, Hugging Face, LangChain, and vector databases . You will collaborate with cross-functional teams to define technical roadmaps, architect high-performing
data + AI solutions , and drive innovation across analytics and enterprise AI platforms. Key Responsibilities Architect and lead implementation of
cloud- data and AI platforms
leveraging Databricks, Delta Lake, and MLflow.
Design
GenAI-powered solutions
using LLM frameworks (Hugging Face, LangChain) and
vector databases
(Pinecone, FAISS, Weaviate, Milvus).
Define architecture for
Retrieval-Augmented (RAG)
pipelines and enterprise-scale chatbot/AI assistant solutions.
Collaborate with data engineers, data scientists, and product stakeholders to transform business requirements into
AI-driven technical solutions .
Integrate Databricks notebooks, Apache Spark, and cloud- services (AWS Glue, Azure Data Factory) for batch and real-time data processing.
Implement
governance and security frameworks
using Unity Catalog, IAM, encryption, and compliance controls.
Define
integration patterns
using APIs, event-driven messaging (Kafka/Pub/Sub), and distributed system design.
Participate in
architectural reviews, performance tuning, and cost optimization
across distributed compute frameworks.
Stay updated on
emerging GenAI, data engineering, and MLOps technologies .
Required Qualifications Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.
10+ years of experience
in enterprise software, data architecture, or AI solution design.
Strong hands-on expertise with
Databricks (Delta Lake, MLflow, Spark, Unity Catalog) .
Proficiency in at least one cloud platform (AWS, Azure, or GCP), with services like S3, ADLS, BigQuery, or Redshift.
Experience building
LLM and GenAI applications
(chatbots, assistants, RAG pipelines).
Familiarity with
Hugging Face, LangChain, and vector databases
(Pinecone, FAISS, Weaviate, Milvus, Chroma).
Experience with streaming platforms (Kafka, Kinesis, Azure Event Hubs).
Strong knowledge of
data modeling, governance, and orchestration tools
(Airflow, dbt, Prefect).
Excellent communication skills for stakeholder management and solution evangelism.
Skills Certifications in
Databricks, AWS/Azure/GCP Solution Architecture, or TOGAF .
Knowledge of
model lifecycle management, versioning, and MLOps practices .
Familiarity with
Generative AI APIs
(OpenAI, Anthropic Claude, Cohere).
Experience with
Unity Catalog, Great Expectations, or other data quality frameworks .
Background in
regulated industries
(finance, healthcare, insurance).
#J-18808-Ljbffr