EverestDX - Python Developer - Generative AI

Description

Key Responsibilities :

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.
  

Model & Data Integration

• Integrate 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.
  

Cloud & Deployment

• 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.
  

Optimization & Scalability

• 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.
  

Required Skills & Qualifications

Core Technical Skills :

• Async programming, REST APIs, and design patterns.
• Libraries : FastAPI, Flask, Pydantic, SQLAlchemy, Pandas, NumPy.
  

Proficiency In AI/GenAI SDKs And APIs

• OpenAI / Azure OpenAI / AWS Bedrock / Hugging Face Transformers.
  

Familiarity With LLM Orchestration

• LangChain, LlamaIndex, Semantic Kernel, CrewAI, or Dust.
• Understanding of embeddings, vector databases, and RAG workflows.
  

Cloud & DevOps Skills

• AWS : Lambda, ECS/EKS, S3, SageMaker, Bedrock.
• Azure : Azure OpenAI, Azure ML, Cognitive Services, AKS.
• Experience with CI/CD, IaC (Terraform/Bicep), and API gateways.
• Knowledge of containerization and cloud security best practices.
  

AI & ML Fundamentals

• Good understanding of :