Assistant Manager - IT

About the Company

WNS, part of Capgemini, is an industry leader harnessing Agentic AI to power intelligent operations and transformational solutions. Serving over 700 clients across ten sectors including Banking, Healthcare, Insurance, Shipping, Logistics, Travel, and Hospitality, WNS combines deep domain expertise with advanced AI-driven platforms and analytics. The company’s mission is to deliver enduring business value through human-centric, intelligent solutions that foster innovation, scalability, adaptability, and resilience in a rapidly changing environment. With three headquarters across four continents, 13 countries of operation, 65 delivery centers, and more than 66,000 employees, WNS leverages extensive reach and expertise to make measurable, meaningful impact.

Job Overview

The role involves designing, developing, and implementing Agentic AI systems that seamlessly integrate into clients’ native applications and workflows. This position requires collaborating closely with client stakeholders and engineering teams to translate business challenges into AI-powered technical solutions.

Key Responsibilities

• Architect and develop multi-step reasoning Agentic AI frameworks aligned with client application needs.
• Train, fine-tune, and assess machine learning and large language models utilizing recognized ML training platforms.
• Engage with clients and internal teams to gather requirements, define solutions, and design technical approaches driven by AI.
• Integrate agentic AI workflows through APIs, SDKs, and platform-specific tools across web, mobile, or enterprise systems.
• Implement Retrieval-Augmented Generation (RAG) pipelines, utilize vector databases, and craft prompt/context engineering enhancements to boost agent performance.
• Lead model evaluation activities by establishing metrics, conducting experiments, and refining systems based on feedback and results.
• Guarantee production readiness focusing on scalability, latency, security, cost-effectiveness, and system observability.
• Collaborate across data engineering, product, and QA teams to deliver robust, well-tested AI functionalities.
• Create comprehensive documentation covering system architecture, model behaviors, and integration blueprints for internal and client use.
• Stay abreast of the evolving agentic AI and machine learning tooling landscape to recommend and adopt pertinent innovations.

Required Skills and Experience

• 3 to 5 years in engineering roles with practical experience in AI and ML application development.
• Hands-on expertise building Agentic AI systems using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar.
• Experience embedding AI/ML features into native client applications across web, mobile, or enterprise platforms via APIs and SDKs.
• Knowledge of ML training environments like SageMaker, Vertex AI, Azure ML, or equivalent for model development lifecycle.
• Proficiency in Python programming; familiarity with JavaScript/TypeScript or native mobile stacks enhances application integration capabilities.
• Solid grasp of LLM concepts including prompt engineering, embeddings, Retrieval-Augmented Generation, and use of vector databases such as Pinecone, FAISS, or Weaviate.
• Experience with cloud infrastructure (AWS, Azure, GCP) and container technologies like Docker and Kubernetes.
• Understanding of MLOps best practices, including model versioning, continuous integration/deployment for ML, monitoring, and observability.
• Strong client communication skills, capable of explaining complex technical solutions to non-technical audiences.
• Previous experience within IT services or consulting settings managing multiple client engagements is highly desirable.

Qualifications

A Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related discipline is required.