Senior Software Engineer (Python, AI/ML & Generative AI)

Job Description:

Job Title: Senior Software Engineer – (Python, AI/ML & Generative AI)

Shift Timings: Should be available till 9-9:30 PM IST

Location: PAN INDIA Remote, Jaipur, Hyderabad, Pune, hybrid

Experience Required: 5 - 7 Years

We are seeking an experienced Senior Software Engineer – AI/ML & Generative AI to design, develop, and deploy intelligent, cloud-native solutions. The ideal candidate will have strong hands-on expertise in machine learning, generative AI, cloud platforms (Azure/AWS), and Python-based backend development. This role involves working closely with business stakeholders, data scientists, and product teams to deliver scalable, secure, and production-ready AI solutions.

Required Technical Skills

AI/ML & Generative AI Development

• Design and implement end-to-end AI/ML pipelines, from business understanding to deployment.
• Develop Generative AI solutions using LLMs (OpenAI/Azure OpenAI/Gemini) for document processing, chatbots, and intelligent automation.
• Implement RAG (Retrieval-Augmented Generation) architectures using LangChain, vector stores, schema validation, and output parsers.
• Build and optimize models for NLP, forecasting, and computer vision use cases.
• Apply machine learning algorithms using Scikit-learn, TensorFlow, and PyTorch

where applicable.

• Has worked with Amazon Bedrock.

Backend & API Development

• Develop scalable backend services and APIs using Python, FastAPI, Flask, and Django.
• Implement data pre-processing, post-processing, validation, and enrichment pipelines.
• Ensure APIs are secure, performant, and production ready.

Cloud & DevOps

• Design and deploy AI solutions on Microsoft Azure, including:
• Azure OpenAI
• Azure Machine Learning
• Azure Functions
• Azure Logic Apps
• Azure Web Apps
• Azure Storage & Delta Lake
• Azure Key Vault
• Azure DevOps & CI/CD pipelines
• Deploy and manage workloads using Docker and serverless architectures.
• AWS services such as EC2, Bedrock, SQS, SNS and S3 for selected workloads.
• Implement authentication and secrets management using Service Principals and Key Vaults.
• Apply MLOps best practices for model lifecycle management and monitoring.

Data, Analytics & Visualization

• Work with relational and cloud databases including Azure SQL Database and PostgreSQL.
• Collaborate with stakeholders to translate business needs into analytical and predictive solutions.