Python Software Developer with Gen AI
- Grid Dynamics
- 5 - 8 years
- Hyderabad
- 2 months ago
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Job Description
Project description1 comment
- 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 lifecyclefrom 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.
Required Qualifications
- 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).
Preferred Qualifications (Nice to Have)
- 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.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: BFSI, Investments & TradingRole Category: BFSI, Investments & Trading - OtherRole: BFSI, Investments & Trading - OtherEmployement Type: Full timeContact Details:
Company: Grid DynamicsLocation(s): Hyderabad+ View Contact
Keyskills: Artificial Intelligence Python Azure Cloud Machine Learning AWS
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