Required Skills: AI/ML , Python, agentic AI frameworks, GenAI

Job Description

Technical Leadership & Architecture 

• Own and define enterprise‑grade GenAI architectures, including RAG pipelines, agentic workflows, prompt orchestration, and multi‑model routing strategies. 
• Drive production readiness for GenAI solutions, ensuring scalability, resilience, observability, and cost efficiency. 
• Lead complex architectural decisions spanning data ingestion, vector databases, model selection, guardrails, latency optimization, and API scalability. 
• Establish reference architectures and reusable patterns to accelerate GenAI adoption across Lines of Business. 
• Enterprise Use‑Case Delivery (FDE Model) 
• Act as a Forward Deployed Principal Engineer, partnering directly with business and product teams to deliver high‑impact GenAI use cases from ideation to production. 
• Translate business problems into well‑defined AI system designs and NFRs, ensuring measurable outcomes. 
• Troubleshoot and resolve complex production issues across non‑prod and prod environments. 
• Influence platform roadmap by feeding real‑world use‑case requirements back into central AI services (e.g., Tachyon). 
• Governance, Risk & Compliance 
• Ensure all AI solutions align with risk, cyber, and model governance standards, including AIRR, data protection, and guardrails. 
• Partner with Cyber, MRM, Legal, and Risk teams to design compliant AI patterns without slowing delivery. 
• Embed security, privacy, and ethical AI principles into solution design by default. 
• Organizational Influence & Mentorship 
• Serve as a recognized GenAI expert across the enterprise—regularly consulted by engineering, architecture, and leadership teams. 
• Mentor senior and staff‑level engineers; raise the technical bar across teams. 
• Contribute to internal communities of practice, architecture reviews, and executive‑level technical discussions. 
• Represent GenAI capabilities in internal innovation forums and knowledge‑sharing sessions 

• 7+ years of software engineering experience, with significant depth in AI/ML or data‑intensive systems. 
• 2+ Years of experience in Python programming language. 
• 2+ Proven experience designing and delivering production‑scale Generative AI systems in an enterprise environment. 
• 2+ years of experience in: 
• LLMs, prompt engineering, and RAG architecture 
• Vector databases and semantic search 
• API‑driven, cloud‑native architectures 
• Distributed systems and performance optimization 

• Strong understanding of non‑functional requirements: security, scalability, resiliency, observability, and cost management. 
• Demonstrated Principal‑level impact: influence across multiple teams, platforms, or business units. 
• Experience operating in highly regulated environments (financial services strongly preferred). 
• Hands‑on experience with agentic AI frameworks and multi‑model orchestration. 
• Prior experience in a Forward Deployed Engineer or embedded engineering model. 
• Ability to communicate complex technical concepts clearly to senior executives and non‑technical stakeholders.