Principal AI Engineer | Onsite

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 

Required Qualifications 

• 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 

Preferred Qualifications 

• 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. 

Compensation, Benefits and Duration

Minimum Compensation: USD 64,000
Maximum Compensation: USD 225,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimat