Saransh Inc
Senior AWS Python Developer (Contract-to-Hire)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AWS Python Developer (Contract-to-Hire) with a pay rate of "unknown" for "unknown" duration. Key skills include Python, AWS, MongoDB, Redis, and experience in building APIs and data ingestion pipelines.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 13, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Austin, TX
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🧠 - Skills detailed
#Python #FastAPI #Cloud #Lambda (AWS Lambda) #Data Storage #MongoDB #AWS (Amazon Web Services) #ML (Machine Learning) #Redis #Storage #API (Application Programming Interface) #GraphQL #Flask #Microservices #Data Ingestion
Role description
• Design and develop Python-based APIs and microservices using frameworks like FastAPI or Flask.
• Integrate with MongoDB for application data storage and implement optimized queries using PyMongo or Motor or LAMBDA.
• Implement Redis caching for performance, rate-limiting, and session management.
• understand basics of AWS cloud practitioner and intro to lambda and step fucntions
• Understand AWS bed rock and have a strong command on using LLMS capabilities -summarization, embeddings, and recommendations into backend services.
• Build data ingestion pipelines for structured and unstructured data using Python.Expose ML outputs through RESTful or GraphQL APIs via API Gateway.
• Design and develop Python-based APIs and microservices using frameworks like FastAPI or Flask.
• Integrate with MongoDB for application data storage and implement optimized queries using PyMongo or Motor or LAMBDA.
• Implement Redis caching for performance, rate-limiting, and session management.
• understand basics of AWS cloud practitioner and intro to lambda and step fucntions
• Understand AWS bed rock and have a strong command on using LLMS capabilities -summarization, embeddings, and recommendations into backend services.
• Build data ingestion pipelines for structured and unstructured data using Python.Expose ML outputs through RESTful or GraphQL APIs via API Gateway.
