Principle Engineer AI

• Architect and build enterprise-scale GenAI platforms with strong focus on reliability, scalability, and security
• Lead development of agentic AI systems, including:
  • Agent orchestration frameworks
  • Multi-agent workflows
  • Tool execution layers
• Design and implement context engineering and memory management frameworks:
  • Short-term and long-term memory
  • Context-aware reasoning systems
• Drive adoption of AI-assisted development tools (e.g., Copilot, Claude Code, Devin) across engineering teams
• Define standards, reusable components, and reference architectures for GenAI solutions
• Collaborate with product, architecture, and business teams to translate use cases into high-impact AI solutions
• Ensure responsible AI practices, governance, and compliance alignment
• Mentor senior engineers and foster AI-first engineering culture

Required Qualifications:

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• Extensive experience in software engineering and distributed systems architecture
• Strong programming expertise in Python (mandatory)
• Proven track record in building GenAI / LLM-based applications
• Experience with agent orchestration frameworks and autonomous systems design
• Deep understanding of:
  • Context engineering
  • Prompt design and optimization
  • Memory management architectures
• Hands-on experience with:
  • LLM APIs and ecosystems
  • Vector databases and retrieval systems
• Experience integrating AI development tools such as:
  • GitHub Copilot
  • Claude Code
  • Devin / similar autonomous coding agents

Desired Qualifications:

• Experience with Google ADK or similar agent development kits
• Expertise in multi-agent system design and coordination
• Familiarity with enterprise AI platform design (RAG, orchestration layers, evaluation frameworks)
• Experience in banking/financial services domain (preferred)
• Strong understanding of MLOps / LLMOps practices
• Exposure to secure and compliant AI systems (PII, risk, governance)

Job Expectations:

• Lead end-to-end ownership of GenAI platform components and solutions
• Drive innovation and adoption of agentic AI across business lines
• Deliver measurable business impact (productivity gains, automation, customer experience improvements)
• Act as a thought leader in GenAI within the organization
• Collaborate with global teams across time zones
  • Influence strategic direction of AI initiatives at enterprise level