About Client:

Our client is an AI-driven fintech platform building an agentic CFO solution for mid-market B2B companies and enterprises. The platform helps finance teams automate and optimize cash-flow operations across receivables, payables, cash forecasting, reconciliation, and financial close processes. By combining operational finance workflows, autonomous AI agents, human approvals, and complete audit trails, the company enables organizations to make accurate, explainable, and compliant financial decisions at scale.

Job Description:

Our client is looking for a highly hands-on Head - AI Engineering to lead the design, development, and scaling of its AI platform and engineering team. The ideal candidate will have deep expertise in Agentic AI, Large Language Models (LLMs), distributed systems, and cloud-native architecture, with a proven track record of building and deploying AI-first products from concept to production.

Key Responsibilities:

- Lead the design, development, and scaling of the company's AI platform and engineering function.

- Architect and build scalable Agentic AI solutions using LLMs, RAG, multi-agent systems, and workflow orchestration.

- Design enterprise-grade backend systems, APIs, cloud infrastructure, and distributed architectures.

- Drive AI model evaluation, prompt engineering, performance optimization, and production deployment.

- Build, mentor, and lead a high-performing AI engineering team while remaining hands-on with architecture and technical decision-making.

- Establish engineering best practices across software architecture, security, scalability, testing, DevOps, and AI governance.

- Collaborate closely with Product and Business teams to deliver innovative AI solutions and accelerate product development.

- Stay updated with the latest advancements in Generative AI, LLMs, Agentic AI, and AI infrastructure.

Qualifications & Experience:

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or a related field.

- 10+ years of software engineering experience, including significant experience building AI-first products.

- Strong hands-on expertise in Python, Go, TypeScript, Java, or similar technologies.

- Deep knowledge of LLMs, Agentic AI, RAG, Prompt Engineering, AI Agents, and AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or AutoGen.

- Experience designing scalable cloud-native architectures on AWS, Azure, or GCP using Docker, Kubernetes, CI/CD, and microservices.

- Strong understanding of distributed systems, enterprise SaaS architecture, APIs, data security, and AI governance.

- Experience building and leading high-performing engineering teams in startup or high-growth environments is highly preferred.

- Excellent leadership, problem-solving, communication, and stakeholder management skills.