Artificial Intelligence Engineer

Role Value Proposition

AI Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate architecting, designing, and implementing the core AI and machine learning (ML) infrastructure that underpins our next-generation business applications . It is an individual contributor role, expected to solve wide ranging business problems.

Experience

10-12+ years of relevant experience

Responsibilities

Design , Develop and manage scalable enterprise AI capabilities that support the AI platform.

Design, train, and optimize machine learning and deep learning models for a variety of business use cases (e.g., SLM, computer vision, predictive analytics, recommendation systems).

Enable seamless integration of AI capabilities into business applications and workflows through APIs, SDKs, and microservices.

Collaborate with multiple partners from Business,Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights)

Develop and maintain CI/CD pipelines for ML models, ensuring automated testing, versioning, deployment, and monitoring in production environments.

Documentation & Knowledge Sharing: Produce clear technical documentation and participate in knowledge sharing to mentor team members and enable

Independently lead design, solutioning & estimations Provide people leadership: coach, develop and engage talent

Technical Skills

Python

Statistics, hypothesis testing, Feature engineering, Modeling

Machine learning frameworks: SCikit-learn, Tensorflow, Pytorch,

Natural language processing (NLP): spacy, Transformers, OCR

Gen AI: Developing, and deploying Generative AI (GenAI) solutions using large language models (LLMs)

Expertise with Retrieval-Augmented Generation (RAG),architectures, including integrating external data sources and vector databases to enhance LLM outputs.

Cloud platforms ( Azure), containerization (Docker, Kubernetes), and orchestration tools

Communication skills, analytical skills, structured problem-solving skills.,

Storytelling skills ,Partner & Stakeholder engagement experience People leadership: talent development & engagement experience