Artificial Intelligence Engineer

Job Locations: Chennai/ Bengaluru/ Hyderabad/ Noida/ Pune

Job Summary

AI Application Developer / AI Engineer Role Overview We are seeking an experienced AI Application Developer / AI Engineer to design, build, and deploy end‑to‑end AI solutions using modern machine learning and generative AI techniques. The role involves working hands‑on with data, models, and production systems to deliver scalable, reliable AI applications—without reliance on code‑assist tools such as GitHub Copilot. Key Responsibilities Design, develop, and deploy end‑to‑end AI applications from data ingestion to production inference. Build data pipelines for data preparation, feature engineering, and model training. Select, train, evaluate, and optimize machine learning and deep learning models. Develop APIs and services to expose AI models for real‑time and batch use cases. Implement monitoring, logging, and model performance tracking in production. Collaborate with product, data, and domain teams to translate business requirements into AI solutions. Ensure AI solutions meet enterprise standards for security, scalability, and responsible AI usage.

Required AI Skill Areas

• 1. Machine Learning & Model Development Strong understanding of supervised and unsupervised learning techniques. Experience with model training, evaluation, and tuning. Ability to select appropriate algorithms based on use case and data characteristics. Familiarity with evaluation metrics and model validation techniques.
• 2. Data Engineering & Feature Engineering Hands‑on experience with data preprocessing, cleaning, and exploratory data analysis. Strong skills in feature engineering and handling real‑world data issues. Proficiency in working with structured and semi‑structured data from multiple sources. Experience using Python libraries such as Pandas and NumPy, along with SQL.
• 3. Generative AI / LLM‑Based Application Development Experience building applications using Large Language Models (LLMs). Strong skills in prompt design, prompt optimization, and template creation. Working knowledge of embeddings, vector search, and Retrieval‑Augmented Generation (RAG). Experience integrating LLM APIs into enterprise applications.
• 4. AI System Design, Deployment & MLOps Ability to design scalable AI architectures for training and inference. Experience deploying models as APIs or services (e.g., using FastAPI or Flask). Understanding of model versioning, monitoring, data drift, and retraining strategies. Familiarity with containerization and cloud deployment concepts

Key Responsibilities:

Architect And Develop Comprehensive Machine Learning Solutions Using Tensorflow And Pytorch, Collaborating with the Team to Ensure Timely and Quality Delivery of Both Products and Sustenance Projects.

2. Serve As A Subject Matter Expert In Machine Learning, Providing Technical Guidance To The Team And Stakeholders, Ensuring Projects Align With Industry Standards And Best Practices.

3. Continuously Upgrade Knowledge By Researching And Integrating New Machine Learning Technologies And Methodologies, Ensuring Solutions Remain Current And Meet Evolving Quality Standards.

4. Mentor And Conduct Training Sessions For Team Members, Ensuring A Robust Knowledge Transfer And A Sufficient Pool Of Skilled Professionals In Machine Learning And Related Technologies.

5. Gather And Analyze Specifications To Deliver Tailored Machine Learning Solutions That Meet The Specific Needs Of The Client Organization, Leveraging A Deep Understanding Of Domain Requirements.

6. Support Competency Development By Envisioning Strategic Propositions, Creating Technical Collaterals, And Performing Market Trend Analyses To Position The Organization As A Leader In Machine Learning.

7. Recommend And Implement Initiatives That Create Client Value, Championing The Adoption Of Industry Best Practices In Machine Learning Deployment And Optimization.

Skills Required:

1. Expert Proficiency In Machine Learning Frameworks Such As Tensorflow And Pytorch.

2. Advanced Knowledge Of Python And Sql For Developing Data-Driven Solutions.

3. Strong Understanding Of Data Modeling, Feature Engineering, And Algorithm Selection In Machine Learning Projects.

4. Excellent Problem-Solving Skills And Ability To Articulate Complex Technical Concepts To Non-Technical Stakeholders.

5. Proven Experience In Leading Technical Teams And Mentoring Junior Professionals.