Python Developer | Gen AI

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

• 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.).

3. 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.

4. 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

Strong expertise in Python (1+ years) with knowledge of:

• 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

Strong hands-on experience in AWS or Azure:

• 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:

• NLP, embeddings, and tokenization.
• Prompt engineering and few-shot learning techniques.
• Model performance metrics (latency, perplexity, accuracy).