Sr AI Engineer

Job Description Summary

We are looking for a technically skilled and impact-driven AI Engineer to design and develop advanced AI models across use cases such as multi-agent systems, (Graph) RAG, computer vision, and tabular prediction tasks. You will contribute across the full lifecycle of model experimentation, optimization, and production-readiness, collaborating closely with Data Engineers who handle orchestration and pipeline infrastructure. Operating from our Global Capability Center in Pune, you will work as part of a global team and play a key role in model innovation, scalable architecture design, and integration into production systems, with clear impact on business performance.

Key Responsibilities Model Development & Optimizatio

• nIndependently design and train robust, reusable AI/ML models using frameworks like Kubeflow, PyTorch, TensorFlow, or HuggingFace
• .Apply advanced techniques in deep learning, NLP, computer vision, and classical ML, ensuring models are explainable and scalable
• .Optimize models for accuracy, speed, and resource efficiency, and collaborate with Data Engineers on deployment readiness. AI/ML System Desig
• nTranslate business use cases into scalable AI model architectures, including design of pre-processing strategies and feature engineering approaches
• .Ensure alignment between data characteristics, model architecture, and expected system behavior in production
• .Collaborate on integration patterns with Data Engineers to embed AI models in downstream workflows. Documentation & Standard
• sWrite clear documentation on model assumptions, architecture choices, evaluation criteria, and recommended usage
• .Contribute to the standardization of model development guidelines within the AI team to ensure reproducibility and traceability

**.

Stakeholder Collaboration & Delive**

• ry

Support scoping and delivery of AI features and enhancements within broader data product initiativ
- es.Partner with domain experts, business stakeholders, and functional analysts to iterate on model design and results interpretati
- on.Adapt solutions based on feedback and performance monitoring, ensuring business value is reali

**zed

Innovation & Capability Buil**

• dingStay up to date on emerging AI/ML methods, tools, and frameworks, and explore how these can improve our modelling practi
• ces.Share findings and contribute to team learning sessions, playbooks, or prototyping initiatives. Security & Compliance i
• n AIDesign models with appropriate data privacy, access control, and bias mitigation considerati
• ons.Ensure models meet compliance, governance, and interpretability standards relevant to the business cont

**ext.

Mentoring & Comm**

• unityMentor junior AI engineers on modelling approaches, model evaluation, and development best pract
• ices.Contribute to a knowledge-sharing culture across the AI, data science, and engineering t

**eams.

Required Qualific**

• ationsBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related
• field.3–5 years of experience designing and implementing AI/ML models in produ
• ction.Strong Python development skills, with deep familiarity with ML/DL libraries (e.g., Kubeflow, PyTorch, TensorFlow, scikit-l
• earn).Demonstrated success with real-world AI use cases, including agents, vision, or foreca
• sting.Understanding of model lifecycle, versioning, monitoring, and deployment-readiness (in coordination with MLOps/ML Engin
• eers).Strong ability to collaborate in cross-functional teams and communicate modelling choices to technical and non-technical audi

**ences.

Preferred**

• SkillsExperience with transformers, embedding techniques, image recognition, or reinforcement le
• arning.Familiarity with Docker and secure deployments via API's for inference integ
• ration.Understanding of data governance and AI ethics prin
• ciples.Ability to collaborate effectively across distributed teams (Europe, US, and
• India).Familiarity with the Cloud, Google Cloud is pr
• eferredUnderstanding of database technologies (OLTP vs OLAP vs graphs vs blob storage vs ..) and experience working with some o

f them.