Jobs via Dice
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 focus on designing Python APIs, integrating MongoDB, and implementing AWS services. Key skills include FastAPI, Flask, Redis, and machine learning. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 14, 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
#Microservices #Redis #Data Storage #Storage #Cloud #MongoDB #Python #Flask #Lambda (AWS Lambda) #FastAPI #API (Application Programming Interface) #AWS (Amazon Web Services) #ML (Machine Learning) #Data Ingestion #GraphQL
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Info Dinamica Inc, is seeking the following. Apply via Dice today!
• 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.
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Info Dinamica Inc, is seeking the following. Apply via Dice today!
• 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.
