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Contract Flutter App Developer Jobs in Chicago, IL

TEKsystems

.Net Developer With Fabric

Wheaton, IL

$70 - $80/hr

... App Services Azure SQL Blob Storage Key Vault Logic Apps Data Engineering Python PySpark Large ... Contract to Hire position based out of Wheaton, IL. Pay and Benefits The pay range for this ...

TEKsystems

.Net Developer With Fabric

Wheaton, IL

$70 - $80/hr

... App Services Azure SQL Blob Storage Key Vault Logic Apps Data Engineering Python PySpark Large ... Contract to Hire position based out of Wheaton, IL. Pay and Benefits The pay range for this ...

Apex Informatics

Site Reliability Engineer

Chicago, IL · On-site

$58.75 - $78/hr

Contract Work authorization: Cannot work with OPT or CPT Rate: 50/hr w2 Work Location (Address ... A person who can establish SRE best practices and supports App teams in maturing SRE principles and ...

Saransh Inc

Sr. Cloud Engineer (Azure) - Only W2

Chicago, IL · On-site

$57.50 - $76.75/hr

Contract (Only W2) Must Have Skills: 1. Jira 2. Azure 3. Datadog Skill Metrics: Jira Datadog Azure ... Identify end to end DevOps solutions, leverage best practices and patterns * Self-starter who can ...

IT America Inc

Networking Cloud Engineering

Libertyville, IL · On-site

$54.25 - $72.50/hr

Contract to Hire Cloud Engineering / Networking Responsibilities: * Develop, Design and implement- Azure Cloud Services: Azure Virtual Machines, App Services, AKS, Functions, Storage, Monitor

PCMI LLC

Staff Engineer

Park Ridge, IL · On-site

$165K - $175K/yr

... contract administration. Our platform automates the entire product lifecycle for customers ... Proven experience with CI/CD pipelines and DevOps practices (Azure DevOps, TeamCity, Octopus)

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All JobsContract Flutter App Developer JobsContract Flutter App Developer Jobs in Chicago, IL

Contract Flutter App Developer information

See Chicago, IL salary details

$17

$54

$87

How much do contract flutter app developer jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for contract flutter app developer in Chicago, IL is $54.23, according to ZipRecruiter salary data. Most workers in this role earn between $43.61 and $62.40 per hour, depending on experience, location, and employer.

What is the difference between Contract Flutter App Developer vs Contract Android Developer?

AspectContract Flutter App DeveloperContract Android Developer
Required CredentialsProficiency in Dart, Flutter SDK, mobile app development experienceProficiency in Java/Kotlin, Android SDK, mobile app development experience
Work EnvironmentRemote or on-site, cross-platform developmentTypically on-site or remote, native Android development
Industry UsageUsed by companies seeking cross-platform appsUsed by companies focusing on native Android apps
Search & Comparison IntentOften compared for cross-platform capabilitiesCompared for native Android expertise

The main difference between a Contract Flutter App Developer and a Contract Android Developer lies in their development focus. Flutter developers create cross-platform apps using Dart, while Android developers specialize in native Android apps using Java or Kotlin. Your choice depends on whether you need a single codebase for multiple platforms or native Android performance.

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Contract Flutter App Developer jobs near you

GCP Gemini AI Developer

Co-Sourcing Partners

Chicago, IL • On-site

Full-time

Re-posted 9 days ago

Job description

Job Title: GCP Gemini AI Developer (3-5 Years Experience)
Location: Remote / Hybrid - Chicago preferred
Employment Type: Contract / Full-Time
Reports To: GCP Technical Lead / AI Program Manager
Purpose
The GCP Gemini AI Developer will design, build, and deploy intelligent applications leveraging Google Cloud's Gemini models and Vertex AI platform. This role exists to operationalize advanced GenAI capabilities - including natural language understanding, multimodal reasoning, and generative automation - within scalable, secure, and production-ready cloud environments.
The developer will work hands-on across data engineering, AI model orchestration, and API integration to create AI-driven business solutions that reduce manual effort, enhance decision-making, and unlock measurable value from enterprise data.
Key Performance Outcomes (6-12 Months) Outcome What Success Looks Like Measurement 1. Gemini-Powered Solutions Deployed Design, develop, and deploy at least two Gemini-based AI solutions (e.g., document summarization, chat agent, or data extraction automation) using Vertex AI + Gemini APIs. Delivered to production with >90% accuracy and <2s response time. 2. Scalable Cloud Architecture Build a modular AI microservices framework using Cloud Run / Cloud Functions with integrated authentication, logging, and monitoring. Reusable components adopted in at least 3 future use cases. 3. RAG / Context-Aware Workflows Implement Retrieval-Augmented Generation (RAG) pipelines combining Gemini + BigQuery or vector databases for knowledge grounding. Demonstrated 25% reduction in hallucination or response variance. 4. Cross-Team Enablement Partner with Data, Automation, and AppDev teams to integrate Gemini AI into existing business workflows (e.g., UiPath, Power Platform, or ServiceNow). Minimum of 2 successful integrations with documented ROI. 5. Continuous Optimization Monitor, retrain, and improve AI models via Vertex AI pipelines and Model Monitoring. Demonstrated 15% performance gain over baseline models. Core Responsibilities
  • Design and deploy Gemini 1.5 Pro/Flash integrations via Vertex AI and Generative AI Studio.
  • Build serverless APIs and backend services for AI workflows using Cloud Run, Functions, or App Engine.
  • Develop data ingestion and preprocessing pipelines using BigQuery, Dataform, and Pub/Sub.
  • Apply prompt engineering and parameter tuning to improve generative model accuracy.
  • Implement RAG pipelines leveraging Vertex Matching Engine or Pinecone.
  • Collaborate with automation and data teams to embed AI into existing business processes.
  • Maintain compliance with security, privacy, and model governance standards.

Technical Environment
Core Google Cloud Services
  • Vertex AI, Generative AI Studio, Gemini API
  • BigQuery, BigQuery ML, Dataform
  • Cloud Run, Cloud Functions, Cloud Storage
  • Pub/Sub, Secret Manager, IAM, Cloud Build

Programming Stack
  • Python or TypeScript (Google Cloud SDKs, google-generativeai, aiplatform)
  • FastAPI / Flask / Node.js
  • LangChain / LlamaIndex for orchestration
  • SQL, Pandas, and Jupyter for data prep

Complementary Tools
  • Terraform (IaC)
  • GitHub / GitLab CI/CD
  • Vertex AI Pipelines & Model Registry
  • Vector DB (Vertex Matching Engine, Pinecone, or Weaviate)

Ideal Profile
  • 3-5 years hands-on GCP development experience with AI/ML exposure
  • Strong working knowledge of Vertex AI, Gemini models, and RAG pipeline design
  • Demonstrated ability to move AI prototypes into production
  • Strong communicator, able to collaborate across automation, data, and cloud teams
  • Curious problem-solver passionate about applied AI innovation

Success Metrics
  • Speed to Delivery: End-to-end deployment within 8-10 weeks per use case
  • Model Effectiveness: >90% accuracy or relevance rating from business stakeholders
  • Scalability: Framework reused for ≥3 additional AI initiatives
  • Business Impact: 25%+ improvement in productivity or efficiency from deployed use cases

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