Senior Data & AI Engineer

Ovii's Interpretation of the Role

The Senior Data & AI Engineer will design, build, and operate end‑to‑end data pipelines and AI solutions on AWS for enterprise customers. The role spans data engineering, machine learning, generative AI, and MLOps, requiring close collaboration with cloud, product, and architecture teams.

Role Snapshot

• Design and maintain scalable data pipelines
• Develop and deploy ML and Generative AI models
• Implement MLOps workflows on AWS
• Collaborate across CloudOps, DevOps, product and architecture
• Mentor junior engineers and interns
• Ensure data governance, security and compliance

Must-Have Requirements

• Python
• AWS Data & AI services
• Machine Learning frameworks
• Big data technologies
• SQL & NoSQL databases
• MLOps tools
• Generative AI frameworks
• Vector databases
• Prompt engineering & RAG
• Data governance & security
• AWS Professional‑level certification
• AWS AI/ML Specialty certification
• Data Engineering
• Machine Learning
• Applied AI
• Bachelor's or Master's in Computer Science, Data Science, AI, Statistics, Mathematics or related technical discipline

Nice-to-Have Signals

• Enterprise AI assistant development
• Computer Vision or advanced NLP experience
• Open‑source contributions
• Hackathon or Kaggle participation
• Familiarity with Agentic AI architectures
• Exposure to multi‑agent systems
• Generative AI
• Agentic AI
• MLOps
• AWS cloud AI services

Work Setup

• Location: Pune, India
• Work mode: ONSITE
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Education requirement details
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Design, build, and optimize data ingestion, transformation, and processing pipelines for structured and unstructured data.
• Create, train, evaluate, and productionize machine‑learning and deep‑learning models for classification, forecasting, recommendation, NLP and other use cases.
• Develop Generative AI applications, RAG solutions, AI assistants and intelligent automation workflows using LLMs and Agentic AI frameworks.
• Implement end‑to‑end MLOps pipelines for model versioning, governance, monitoring and automated retraining.
• Architect cloud‑native AI and analytics solutions on AWS, leveraging SageMaker, Bedrock, Glue, Athena, Redshift and related services.
• Engage with customers to translate business requirements into scalable data and AI architectures and present solutions to technical and non‑technical audiences.
• Collaborate with CloudOps, DevOps, product and architecture teams to operationalize AI workloads.
• Mentor junior engineers, document best practices, and contribute reusable frameworks and accelerators.

Good Fit If You Have

• Hands‑on experience with Generative AI frameworks such as LangChain or Hugging Face.
• AWS Professional‑level or AI/ML Specialty certification.
• Contributions to open‑source AI projects or participation in hackathons/Kaggle competitions.