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Python Developer @ Grid Dynamics

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Grid Dynamics  Python Developer

Job Description

  • Core Backend Development: Design, build, and maintain scalable backend services and APIs using Python (FastAPI/Django/Flask).

  • Agentic AI Implementation: Architect and develop autonomous AI agents capable of multi-step reasoning, tool use, and complex decision-making to automate business workflows.

  • GenAI & RAG Integration: Build and optimize Retrieval-Augmented Generation (RAG) pipelines to ground LLMs in proprietary data, ensuring high accuracy and low latency.

  • Production Deployment: Take ownership of the full software lifecycle from architectural design to deployment and maintenance in a production environment. Monitor system health, performance, and reliability.

  • Tooling & Orchestration: Integrate Generative AI tools (e.g., OpenAI, Anthropic, LangChain, LlamaIndex) into existing application logic.

  • Collaboration: Work closely with frontend engineers, data scientists, and product managers to translate complex AI capabilities into user-friendly features.




  • Essential functions


    • Strong Python Proficiency: Deep understanding of Python internals, asynchronous programming, and modern web frameworks.

    • Production Experience: Proven track record of deploying and maintaining at least one application in a production environment. You know what it takes to keep a system running (logging, monitoring, error handling).

    • GenAI & Agentic Mindset: Hands-on experience with Generative AI tools and a conceptual understanding of how to build systems where AI models act as "agents" rather than just text generators.

    • Database Skills: Proficiency with SQL (PostgreSQL, MySQL) and experience with vector databases (Pinecone, Weaviate, Milvus, or pgvector).




    Qualifications


    • Core Backend Development: Design, build, and maintain scalable backend services and APIs using Python (FastAPI/Django/Flask).

    • Database Skills: Proficiency with SQL (PostgreSQL, MySQL) and experience with vector databases (Pinecone, Weaviate, Milvus, or pgvector).
      GenAI & RAG Integration: Build and optimize Retrieval-Augmented Generation (RAG) pipelines to ground LLMs in proprietary data, ensuring high accuracy and low latency.




    Would be a plus



    • Hands-on RAG & Agent Build: Demonstrated experience specifically building RAG architectures or functional AI Agents that interact with external APIs/tools.

    • Data Science/ML Background: Familiarity with machine learning concepts, model evaluation, or data engineering pipelines is a strong plus.

    • Cloud Native: Experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).

    • Prompt Engineering: Advanced skills in prompt optimization and steering LLM behavior.




    We offer




    • Opportunity to work on bleeding-edge projects

    • Work with a highly motivated and dedicated team

    • Competitive salary

    • Flexible schedule

    • Benefits package - medical insurance, sports

    • Corporate social events

    • Professional development opportunities

    • Well-equipped office




    Job for Automation

    Job Classification

    Industry: IT Services & Consulting
    Functional Area / Department: Engineering - Software & QA
    Role Category: Software Development
    Role: Data Platform Engineer
    Employement Type: Full time

    Contact Details:

    Company: Grid Dynamics
    Location(s): Hyderabad

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    Keyskills:   Backend orchestration data science Postgresql Django MySQL Machine learning Architectural design SQL Python

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    Grid Dynamics

    About Us: Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, and advanced analytics services. Fusing technical vision with business acumen, we enable positive business outcomes for enterprise companies undergoing business tran...