Cloudera

1 month ago

AI Solutions Architect - FS or CI Polygraph Required

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Technical architect and execution lead for government agencies, designing, building, and deploying AI applications on CDP. Leads end-to-end data engineering, model selection, and MLOps in secure, air-gapped or hybrid-cloud environments. Collaborates with the AI Center of Excellence to establish guardrails for ethics, bias mitigation, and FedRAMP/IL5 compliance, and translates complex AI concepts for GS-level stakeholders.

Location: Virginia

Workplace: Remote

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•AI Model Strategy, Selection and Implementation: Evaluate and select optimal model architectures (LLMs, SLMs, or traditional ML) and guide Build/Buy/Fine-tune decisions emphasizing open-source options that can run securely within sovereign perimeters.
•End-to-End Data Engineering: Design and implement robust data pipelines within CDP to transform legacy data into AI-ready formats; optimize vector databases and RAG architectures; build data pipelines with Spark, Nifi, Kafka, or similar ETL tools.
•Optimization & Performance Tuning: Optimize model inference in production using quantization, pruning, and hardware acceleration; implement LLMOps to monitor performance, detect hallucinations, and manage versioning and drift.
•Public Sector Advisory & Governance: Collaborate with AI CoE to establish automated guardrails for ethics, bias mitigation, and FedRAMP/IL5 compliance; translate complex AI concepts for GS-level stakeholders.
•Security & Compliance Focus: Work in highly secure/air-gapped environments and ensure compliance with government security frameworks (NIST AI RMF, FedRAMP, SRGs, STIGs)

Pay and Benefits

Perks:Unplugged DaysRemote WorkWellness Stipend

Key Requirements

•5+ years in Data Engineering, Machine Learning, or Software Engineering, with at least 2 years focused on Generative AI or Deep Learning.
•Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, Hugging Face).
•Hands-on experience with Cloudera (CDP), Spark, or similar big data ecosystems.
•Proficiency with orchestration tools like LangChain, LlamaIndex, or Haystack.
•Experience developing visual data representations and dashboards (Django, React, or Angular) and with JVM languages (Java, Scala).

Experience:5+ yearsGovernmentPublic sectorAIData engineering

Skills:PythonProblem-solvingCommunicationTeamwork

Tech Stack:PythonPyTorchTensorFlowHugging FaceCDPSparkNifiKafkaLangChainLlamaIndexHaystackDjangoReactAngularJavaScalaPineconeMilvusPGVectorNVIDIA

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Security Clearance:Top Secret

Company Brief

Cloudera

Provides a hybrid data platform for managing, analyzing, and securing enterprise data across cloud and on-premises environments, enabling machine learning, analytics, and data engineering at scale.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 2008

Glassdoor: 3.8

Website LinkedIn

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Cloudera

1 month ago

AI Solutions Architect - FS or CI Polygraph Required

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: Virginia

Workplace: Remote

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•AI Model Strategy, Selection and Implementation: Evaluate and select optimal model architectures (LLMs, SLMs, or traditional ML) and guide Build/Buy/Fine-tune decisions emphasizing open-source options that can run securely within sovereign perimeters.
•End-to-End Data Engineering: Design and implement robust data pipelines within CDP to transform legacy data into AI-ready formats; optimize vector databases and RAG architectures; build data pipelines with Spark, Nifi, Kafka, or similar ETL tools.
•Optimization & Performance Tuning: Optimize model inference in production using quantization, pruning, and hardware acceleration; implement LLMOps to monitor performance, detect hallucinations, and manage versioning and drift.
•Public Sector Advisory & Governance: Collaborate with AI CoE to establish automated guardrails for ethics, bias mitigation, and FedRAMP/IL5 compliance; translate complex AI concepts for GS-level stakeholders.
•Security & Compliance Focus: Work in highly secure/air-gapped environments and ensure compliance with government security frameworks (NIST AI RMF, FedRAMP, SRGs, STIGs)

Pay and Benefits

Perks:Unplugged DaysRemote WorkWellness Stipend

Key Requirements

•5+ years in Data Engineering, Machine Learning, or Software Engineering, with at least 2 years focused on Generative AI or Deep Learning.
•Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, Hugging Face).
•Hands-on experience with Cloudera (CDP), Spark, or similar big data ecosystems.
•Proficiency with orchestration tools like LangChain, LlamaIndex, or Haystack.
•Experience developing visual data representations and dashboards (Django, React, or Angular) and with JVM languages (Java, Scala).

Experience:5+ yearsGovernmentPublic sectorAIData engineering

Skills:PythonProblem-solvingCommunicationTeamwork

Tech Stack:PythonPyTorchTensorFlowHugging FaceCDPSparkNifiKafkaLangChainLlamaIndexHaystackDjangoReactAngularJavaScalaPineconeMilvusPGVectorNVIDIA

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Security Clearance:Top Secret

Company Brief

Cloudera

Provides a hybrid data platform for managing, analyzing, and securing enterprise data across cloud and on-premises environments, enabling machine learning, analytics, and data engineering at scale.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 2008

Glassdoor: 3.8

Website LinkedIn