🎯 Role Overview

A hands-on technical leadership role combining AI engineering, solution architecture, and team mentoring. Directly responsible for designing, building, and deploying production-grade Generative AI solutions (LLMs, RAG, Agentic workflows) in a regulated financial domain.

📋 Key Responsibilities

• Architecture & Delivery: Architect and deliver end-to-end LLM applications, RAG pipelines, and agentic workflows. Own critical decisions on model selection, retrieval strategies, integration, cost, and latency optimization.

• Quality & Operations: Implement evaluation, regression testing, tracing, and monitoring frameworks. Ensure solutions meet enterprise requirements for security, reliability, data privacy, and compliance (e.g., preventing prompt injection and data leaks).

• Stakeholder Alignment & Leadership: Translate complex business, risk, and compliance requirements into practical tech architectures. Mentor engineering teams and establish reusable AI standards and patterns.

🎯 Requirements

• Experience: 6+ years in software/AI engineering, including recent hands-on experience delivering GenAI applications into production. Domain background in banking, fintech, payments, lending, or risk/compliance is a strong plus.

• Technical Skills: Strong Python and software engineering fundamentals (system design, APIs, testing). Proficiency in RAG, vector databases, reranking, tool calling, and agent frameworks (e.g., LangChain, LangGraph, LlamaIndex).

• Infrastructure & Security: Solid grasp of cloud platforms, containers, CI/CD, observability, and AI security risks/guardrails.

• Leadership & Soft Skills: Strong English communication; proven track record of mentoring engineers and collaborating directly with client stakeholders.