You will be taken to Sonata Software’s own careers page to apply. Job ID Qcspl-26-27-26.
Job description
Job Title : AI/ML Engineer Location: Pune | Hybrid Experience: 6–8 Years Primary Skills: Python, SQL, Machine Learning, ML Modelling, Agentic AI About the Role We are looking for an experienced AI/ML Engineer to join our AI Engineering team and build intelligent, scalable, and production-ready AI/ML solutions. The role will focus on designing, developing, deploying, and optimizing Machine Learning models and Agentic AI solutions that deliver measurable business value across customer-facing and operational workflows. The ideal candidate should have strong hands-on experience in Python, Machine Learning, SQL, MLOps, and Agentic AI frameworks, along with the ability to translate business requirements into scalable AI solutions. Key Responsibilities Machine Learning Solution Development
Design, develop, and deploy Machine Learning models for prediction, recommendation, optimization, classification, and forecasting use cases.
Build scalable ML pipelines covering data preparation, feature engineering, model training, evaluation, and deployment.
Apply statistical and machine learning techniques to solve business problems using structured and semi-structured data.
Work closely with product, engineering, and business teams to translate requirements into production-ready AI/ML solutions.
Agentic AI Development
Design and develop agentic workflows using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or similar.
Develop AI agents capable of reasoning, task orchestration, tool usage, and multi-step workflow execution.
Integrate AI agents with enterprise systems, APIs, databases, and business applications.
Combine Agentic AI capabilities with predictive and analytical ML models.
Data Engineering & Integration
Build and maintain data pipelines to ingest, transform, and process data from enterprise systems, APIs, databases, and external sources.
Develop reusable data services and ML components to accelerate solution delivery.
Ensure data quality, reliability, and scalability for model development and production workloads.
MLOps & Productionization
Implement CI/CD pipelines for ML models and AI services.
Establish model monitoring, performance tracking, retraining, and deployment processes.
Manage model lifecycle, experimentation, versioning, and governance.
Support deployment of AI/ML workloads on cloud platforms.
Engineering Excellence
Follow best practices for software engineering, testing, observability, and documentation.
Leverage AI-assisted development tools to improve engineering productivity.
Contribute to reusable frameworks, standards, and best practices across the AI team.
Required Qualifications
6–8 years of software engineering experience with strong Python development skills.
3+ years of hands-on experience building and deploying Machine Learning solutions.
Hands-on experience building Agentic AI solutions using LangGraph, LangChain, AutoGen, CrewAI, or similar frameworks.
Strong understanding of supervised and unsupervised learning techniques.
Experience with recommendation systems, predictive analytics, forecasting, classification, anomaly detection, or optimization.
Hands-on experience with Scikit-Learn, XGBoost, LightGBM, TensorFlow, PyTorch, or equivalent frameworks.
Strong SQL and data analysis skills.
Experience with feature engineering, model evaluation, and experimentation frameworks.
Familiarity with MLOps practices, model deployment, monitoring, and lifecycle management.
Experience building data pipelines and integrating enterprise systems through APIs and databases.
Experience with Docker, CI/CD, Git, and modern software engineering practices.
Experience working with AWS or Azure cloud platforms.
Strong analytical, problem-solving, and communication skills.
Good to Have Advanced AI & Data Platforms
Experience with optimization techniques, routing algorithms, scheduling, or Operations Research.
Knowledge of demand forecasting, customer propensity modelling, pricing analytics, and recommendation engines.
Experience with explainable AI, model evaluation frameworks, and experimentation methodologies.
Data & Analytics
Experience with Snowflake, Databricks, or modern cloud data platforms.
Experience building analytical dashboards and decision-support solutions.
Familiarity with large-scale data processing and distributed computing.
Generative AI
Exposure to LLMs, RAG architectures, vector databases, and Agentic AI frameworks.
Experience integrating ML solutions with Generative AI applications.
Domain Knowledge Exposure to Sales, Pricing, Customer Intelligence, E-commerce, Distribution, Logistics, Supply Chain, or ERP/CRM ecosystems is preferred. Technology Stack AreaTechnologies ProgrammingPython, SQL ML FrameworksScikit-Learn, XGBoost, LightGBM, TensorFlow, PyTorch Agentic AILangGraph, LangChain, AutoGen, CrewAI Generative AILLMs, RAG, Vector Databases DataSnowflake, SQL, APIs, Data Pipelines MLOpsMLflow, Docker, CI/CD, Model Monitoring CloudAWS, Azure Development ToolsGitHub, Azure DevOps, GitLab, GitHub Copilot, Cursor
About Sonata Software Sonata Software is an AI-first modernization engineering company that helps enterprises transform legacy systems into intelligent, scalable business platforms. Powered by its Platformation™ framework and Harmoni.AI platform, Sonata delivers AI-led modernization across cloud, data, AI, Dynamics, test automation, and managed services. Headquartered in Bengaluru, India, Sonata has more than $1.2 billion in revenue and 6,400+ AI engineers supporting global delivery across regions including the US, UK, India, Malaysia, Mexico, Australia, DACH, and the Nordics. With deep partnerships across Microsoft, AWS, Salesforce, and Snowflake, Sonata helps Fortune 500 enterprises accelerate innovation, improve efficiency, and drive sustainable growth. Website:www.sonata-software.comm
