Senior Software Engineer – (python, Ai/ml & Generative Ai)

Programmers.io

Hyderabad, TelanganaFull-timeMid LevelOn-site

Job Description

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.

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