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Python Developer | Gen AI
PIXELOTECHpushkar, gujarat, in7 days ago
Job descriptionIntegrate models via APIs from OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or Hugging Face. Preprocess and vectorize text data using transformers, sentence embeddings, or custom tokenizers. Work with vector databases such as Pinecone, FAISS, Milvus, Weaviate, or Amazon OpenSearch. Collaborate with data engineers to connect structured and unstructured datasets (S3, Cosmos DB, SQL, etc.). Containerize GenAI services using Docker and deploy on Kubernetes (EKS / AKS). Automate deployment pipelines using GitHub Actions, Azure DevOps, or Terraform. Implement logging, monitoring, and model telemetry using CloudWatch, Application Insights, or Prometheus. Ensure secure API management and key handling via AWS Secrets Manager or Azure Key Vault. Optimize inference latency and cost for LLM-based applications. Implement caching, batching, and token management strategies. Fine-tune or adapt models for domain-specific applications. Apply AI guardrails and output moderation for responsible AI use. Async programming, REST APIs, and design patterns. Libraries : FastAPI, Flask, Pydantic, SQLAlchemy, Pandas, NumPy. OpenAI / Azure OpenAI / AWS Bedrock / Hugging Face Transformers. LangChain, LlamaIndex, Semantic Kernel, CrewAI, or Dust. AWS : Lambda, ECS / EKS, S3, SageMaker, Bedrock. Azure : Azure OpenAI, Azure ML, Cognitive Services, AKS. NLP, embeddings, and tokenization. Prompt engineering and few-shot learning techniques. Model performance metrics (latency, perplexity, accuracy).
Job Title : Sr. Python Developer - Gen AI
Job Type : Full Time
Experience : 1+
Notice Period - Immediate to 15 days joiners are highly preferred
Key Responsibilities :
1. Application Development
- Design and develop GenAI-enabled microservices and APIs using Python (FastAPI, Flask, Django).
- Implement LLM integrations using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI.
- Build and manage RAG pipelines combining embeddings, vector stores, and retrieval mechanisms.
- Develop prompt templates and implement prompt chaining / orchestration for conversational AI systems.
2. Model & Data Integration
3. Cloud & Deployment
4. Optimization & Scalability
Required Skills & Qualifications
Core Technical Skills
Strong expertise in Python (1+ years) with knowledge of :
Proficiency in AI / GenAI SDKs and APIs :
Familiarity with LLM orchestration :
Understanding of embeddings, vector databases, and RAG workflows.
Cloud & DevOps Skills
Strong hands-on experience in AWS or Azure :
Experience with CI / CD, IaC (Terraform / Bicep), and API gateways.
Knowledge of containerization and cloud security best practices.
AI & ML Fundamentals
Good understanding of :
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