Applied AI Engineer – Agentic Solutions

Experience Level: Mid Senior

Practice Area: AI Engineering

Engagement Type: Full Time

Industry: Financial Services & Insurance (FSI)

Location: Global Development Centre (GDC) - Onsite

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Role Summary

We are seeking an Agentic AI Solutions Applied Engineer to design, prototype, and build next-generation agentic AI solutions across search, retrieval, orchestration, and agentic automation. This role focuses on hands-on engineering using MCP Server patterns, enterprise-grade RAG pipelines, Google File Search and cloud-native AI platforms capabilities. You will work closely with the AI enterprise architects, data engineers, and scrum master to deliver scalable AI systems that support enterprise clients with Financial Services & Insurance (FSI). Demonstrable experience with agentic frameworks and similar applied solutions is essential.

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The Difference You’ll Make

In this role you will help enterprise clients transition from experimental AI to reliable, production-grade agentic solutions. Your work will enhance customer-facing chatbot experiences across superannuation, insurance, and banking by enabling AI systems to reason over customer information and act through agentic capabilities. By combining MCP Server, RAG, and cloud-native AI platforms into practical workflows, you will directly support faster claims processing, quicker inquiry resolution, and more efficient customer service interactions for financial services clients.

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Key Responsibilities

• Design, build, and optimise agentic AI workflows using MCP Server patterns in production environments.
• Develop enterprise-grade RAG pipelines including vector search, retrieval optimisation, and grounding logic.
• Integrate Google File Search, Azure Foundry, and other cloud-native AI components into existing system architectures.
• Implement orchestration frameworks for multi-step agents, tool use, and automated reasoning.
• Develop APIs and backend services for AI inference, retrieval calls, and agent-tool interactions.
• Collaborate with architecture and engineering teams to align on design patterns, performance optimisation, and governance controls.
• Conduct testing, evaluation, and continuous improvement of AI agents in real-world scenarios.
• Analyse product and business requirements to translate them into agentic workflows and technical features.
• Design and integrate secure network and connectivity patterns for AI agent workflows, including PrivateLink, API Management, VPC/VNet configurations, and controlled egress paths.
• Produce clear technical documentation, design artefacts, and integration guides for internal and client platforms.
• Support knowledge transfer, internal engineering uplift, and practice development across the AI Engineering group.

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Required Skills and Competencies

• Proven hands-on experience delivering Agentic AI solutions in enterprise environments
• Experience deploying AI workflows on Azure Foundry
• Practical experience implementing MCP Server-based patterns, tool calling, or equivalent frameworks
• Experience with Google File Search, Vertex AI Search, or similar technologies
• Strong understanding of RAG architectures, including query transformation, reranking, vector storage, and chunking strategies
• Proficiency with Python and common LLM or AI libraries such as LangChain, LangGraph, HuggingFace, OpenAI, and Anthropic
• Understanding of vector databases such as Pinecone, Chroma, and FAISS, and embedding optimisation
• Familiarity with LLM agent frameworks and tool-use design patterns
• Practical experience implementing secure network and connectivity controls such as PrivateLink, APIM, VPC/VNet networking, and service-to-service integration for AI workloads.
• Strong API engineering skills and experience with cloud-native microservices
• Experience with architectural frameworks and industry standards including:
• Google File Search
• Azure AI and OpenAI governance patterns
• Responsible AI guidelines

• Strong problem-solving skills and an organised, structured engineering approach
• Ability to work independently and collaborate with global teams

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Qualifications and Experience

• 3–5 years’ experience in software engineering or applied AI development
• Prior experience delivering AI agents, RAG systems, or Google File Search integrations
• Experience working across cloud environments such as Microsoft Azure Foundry, Google Cloud, or AWS
• Exposure to agentic development lifecycle standards and engineering best practices
• Previous consulting experience is preferred but not required

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What We Offer

• Competitive salary with performance-based incentives
• Opportunity to work on real applied AI solutions used by enterprise clients
• Professional growth within a dynamic consulting environment
• A collaborative culture with global exposure and cross-functional teamwork

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