About the Role

We are seeking an experienced Senior Product & Application Engineer to join our team. The ideal candidate will have a strong background in building and shipping end-to-end data-driven and AI-powered applications from backend engineering and data pipelines through to integrating AI models, user-facing features and production deployment.

Key Responsibilities

- Design, build and ship production-grade data and AI-powered applications owning the full stack from data ingestion and AI model integration through to application logic and user-facing interfaces.

- Develop scalable backend services and APIs to power data quality, validation, analytics and AI model serving features accessible to business users.

- Build and maintain automated data pipelines for ingestion, transformation, quality validation and delivery of structured datasets.

- Implement application features including data quality dashboards, self-serve insights, automated flagging and summary reporting at varying levels of granularity.

- Ensure robust data governance within the application audit trails, access control, lineage tracking and reproducible workflows.

- Collaborate with cross-functional teams’ analysts, data scientists and business stakeholders to translate requirements into product features.

- Support deployment and integration of the application on enterprise or client infrastructure.

- Integrate, evaluate and deploy AI/ML models into production applications — including LLM-based workflows,



embedding pipelines and prompt engineering — ensuring reliability and performance at scale.

Qualifications

- 5+ years of proven experience in product or application engineering, with a track record of shipping production software not just prototyping.

- Strong proficiency in Python and backend application development;

experience with REST APIs, application frameworks, and AI/ML libraries such as LangChain, OpenAI SDK, or HuggingFace Transformers.

- Solid understanding of data engineering fundamentals pipelines, transformations, schema validation and data quality.

- Experience building user-facing data and AI-powered products consumed by non-technical business users, with a focus on making AI capabilities accessible and actionable.

- Familiarity with SQL and working with structured, multi-source datasets.

- Strong problem-solving skills with the ability to work across the full application stack.

- Excellent communication skills, with the ability to explain technical decisions clearly to non-technical stakeholders.

- Ability to work independently and take end-to-end ownership in a fast-paced, product-driven environment.

- Experience with cloud deployment on Azure, AWS or GCP is a robust plus including containerisation, environment setup, managed services and deploying AI/ML model endpoints in production.

Qualifications

- B.Tech / B.E. (Computer Science, IT, or related field)• M.Tech / MCA (Preferred)• M.Sc. (Statistics / Mathematics / Data Science)

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