Lead AI Engineer
Summary
Lead a team to design, build, and integrate AI capabilities—including GenAI, RAG, and Agentic AI—into a finance-focused platform using cloud-native tools and AI frameworks.
Lead AI Platform Engineer
Experience: 12+ Years
Role Overview
We are seeking a highly experienced Lead AI
Platform Engineer to drive the engineering and implementation of AI
capabilities within a Finance AI platform. This is a hands-on technical
leadership role focused on establishing scalable AI engineering patterns,
accelerating delivery, and mentoring development teams. The ideal candidate
will combine strong cloud-native engineering expertise with practical
experience building and integrating GenAI and Agentic AI solutions into
enterprise platforms.
Key Responsibilities
- Lead the implementation of AI-enabled applications and platform
capabilities.
- Establish reusable patterns, frameworks, and best practices for
AI engineering.
- Design and oversee LLM, RAG, and Agentic AI integrations within
enterprise environments.
- Collaborate with architects and engineering teams to ensure
scalable, secure, and maintainable solutions.
- Define standards for AI observability, governance, security,
and performance.
- Mentor engineers and provide technical leadership across AI
development initiatives.
- Contribute hands-on to solution design, development, code
reviews, and production deployment.
Required Skills
- 12+ years of software engineering experience, with strong
expertise in Java and/or Python.
- Proven experience building cloud-native applications on Azure,
AWS, or GCP.
- Strong knowledge of Kubernetes, Microservices, APIs,
Event-Driven Architecture, and DevOps practices.
- Hands-on experience with LLM integration, RAG architectures, AI
orchestration frameworks, and Agentic AI solutions.
- Experience with AI frameworks and tools such as LangChain,
LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent.