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Agentic AI

Agentic AI

CapcoIndia
6 days ago
Job description

This job is with Capco, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery.

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

MAKE AN IMPACT

We are seeking a highly skilled .NET or Python Developer with expertise in Artificial Intelligence, Retrieval-Augmented Generation (RAG) integration, and Model Context Protocol (MCP). The candidate will be responsible for developing scalable applications, building intelligent search and conversational systems, and enabling seamless interaction between enterprise systems and LLMs using RAG + MCP pipelines.

Key Responsibilities :

Design, develop, and maintain applications in

  • .NET (C#)

or

Python .

Implement

RAG pipelines

by integrating

LLMs (OpenAI, Azure OpenAI, Hugging Face, LangChain, LlamaIndex, etc.)

with enterprise and external data sources.

Develop

MCP-based integrations

to connect tools, APIs, and enterprise data systems with LLMs.

Build APIs and microservices for

AI-powered search, summarization, and conversational AI .

Create

document ingestion pipelines

(PDFs, databases, SharePoint, etc.) and manage embeddings with

vector databases (Pinecone, Weaviate, FAISS, Qdrant, Azure Cognitive Search, etc.) .

Collaborate with AI engineers, architects, and data teams to ensure scalable deployment of RAG / MCP solutions.

Optimize application

performance, security, and scalability

for production-grade AI systems.

Stay updated with

AI frameworks, MCP standards, and cloud AI services .

Required Skills & Experience :

Minimum of 8 years of IT experience with 1+ years of AI experience

Strong hands-on experience in

  • .NET (C#)
  • or

    Python .

    Solid understanding of

    OOP, REST APIs, and microservices architecture .

    Proven experience with

    LLM-based applications

    and

    RAG (Retrieval-Augmented Generation)

    integration.

    Knowledge and practical implementation of

    Model Context Protocol (MCP)

    for AI tool orchestration.

    Familiarity with

    vector databases

    (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search).

    Hands-on experience with

    LangChain, LlamaIndex, Hugging Face Transformers , or similar AI libraries.

    Strong problem-solving and cross-functional collaboration skills.

    Good to Have : Experience with

    containerization (Docker, Kubernetes) .

    Experience with

    cloud AI services (Azure, AWS, GCP)

    for deployment and scaling.

    Exposure to

    SQL / NoSQL databases

    for structured and unstructured data.

    Prior experience in

    chatbot development, enterprise search, or knowledge management systems .

    Understanding of

    MLOps practices

    for AI model deployment and monitoring.

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