3-6 Full time About the Role We are looking for AI Engineers to design and build nextgeneration AI copilots and agentic systems for the wealth management and financial advisory domain. You will work at the intersection of LLMs, financial workflows, and user experience, building intelligent assistants that augment advisors, automate workflows, and enhance client engagement. This role requires strong handson expertise in LLM systems, deep understanding of enterprisegrade AI architecture, and the ability to translate complex financial use cases into scalable AI products.

What You Will Do Design and build AI copilots Architect and develop AI copilots for financial advisors, client servicing, and internal operations Build multistep agentic workflows using LLMs, tools, memory, and orchestration frameworks Develop productiongrade LLM systems Implement RetrievalAugmented Generation (RAG), semantic search, and grounded responses Design prompt strategies, evaluation pipelines, and guard rails for accuracy and compliance Own endtoend AI solution lifecycle From PoC to production deployment with scalability, reliability, and observability Optimize latency, cost, and response quality of LLM systems Integrate AI into enterprise ecosystems Embed copilots into CRM, advisor platforms, communication tools, and workflow systems Work with APIs, eventdriven systems, and microservices Collaborate crossfunctionally Partner with Product, UX, and domain experts in wealth management Translate advisor and client needs into AI capabilities and user journeys Drive AI innovation Evaluate emerging LLM models, agent frameworks, and tooling Contribute to AI architecture standards, reusable components, and internal platforms What We Are Looking For Core Experience 610 years in software engineering,



with 3 years in AI/ML and LLMbased systems Strong experience building LLMpowered applications in production environments Proven track record of delivering endtoend AI products, not just experiments Technical Skills Languages: Python (preferred), TypeScript or C# LLM &

- AI Stack: OpenAI / Azure OpenAI / Anthropic or equivalent RAG architectures, embeddings, vector databases: Pinecone, Qdrant, Azure AI Search Prompt engineering, evaluation frameworks, hallucination control Agentic Frameworks: LangChain, LlamaIndex, CrewAI, or similar orchestration frameworks Experience designing multiagent or toolusing systems Cloud &
- Architecture: Azure (preferred) or AWS/GCP Microservices, APIs, eventdriven systems Experience with scalable, distributed systems DevOps &
- Production Readiness: CI/CD pipelines, monitoring, logging, and observability Model evaluation, A/B testing, and performance tuning Domain &
- Product Orientation Strong interest or experience in wealth management, financial advisory, or fintech Understanding of: Clientadvisor workflows Financial documents, compliance constraints, and data sensitivity Ability to build usercentric AI systems, not just backend models Preferred Experience Experience building AI copilots or conversational assistants in enterprise settings Exposure to Microsoft ecosystem (Azure AI, Microsoft 365, Teams, Graph API) Experience integrating with CRM systems (e.g., Salesforce) and workflow automation tools Familiarity with evaluation frameworks, guard rails, and responsible AI practices Prior work in AI platforming, reusable AI components, or AI CoE setups What Success Looks Like AI copilots are actively used by advisors and internal teams Solutions demonstrate high accuracy, low hallucination, and strong adoption Systems are scalable, secure, and compliant with financial domain requirements Clear impact on productivity, client experience, and business outcomes Required Skills LLM Artificial Intelligence Platforms prompt engineering .

📌 Senior Engineer & AI Engineering (Ernakulam)
🏢 CogniCor
📍 Ernakulam