Deputy Manager-Data Engineering at WNS Global Services

Noida, Uttar Pradesh, India -

Full Time

Start Date

Immediate

Expiry Date

05 Aug, 26

Salary

0.0

Posted On

07 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Backend Engineering, REST APIs, LangChain, OpenAI SDK, HuggingFace Transformers, Data Engineering, SQL, Azure, AWS, GCP, Containerization, Prompt Engineering, LLM Workflows, Data Pipelines, AI Model Integration

Industry

Business Consulting and Services

Description

Company Description WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees. Job Description 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 strong 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)

Responsibilities

Design and deploy production-grade data and AI-powered applications, managing the full stack from data ingestion to user interfaces. Develop scalable backend services, automated data pipelines, and integrate LLM-based workflows to provide actionable business insights.