egen - Principal AI Engineer
Requirements
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. • 10+ years in software / AI / ML engineering, with a substantial track record of AI systems delivered to production at scale. • Demonstrated technical leadership — owning architecture and setting direction across engagements or teams, not just individual deliverables. • Proven track record of deploying GenAI and/or agentic products to production environments. • Experience with classic machine learning (neural nets, training, tuning) strongly preferred; foundation-model or novel-model work a distinct plus. • Strong data engineering and SQL knowledge. • Senior client-facing experience — translating technical complexity into business value for executive stakeholders. • ## Personal Attributes: • Ownership at scale: You take responsibility not just for your code, but for the outcome of the system and the success of the team building it. • Curiosity: The AI landscape changes weekly; you stay at the frontier and bring the team with you. • Consultative authority: You earn the trust of client leadership and are the calm, credible technical voice in a high-stakes room. • Ethics: You hold the line on responsible AI development and data privacy.
Responsibilities
• Set technical direction: Own architecture for our most complex GenAI and agentic systems end-to-end, and set the standards — evaluation, observability, responsible AI — that the practice builds to. • Build at the frontier, hands-on: Stay in the code where it matters most — foundation-model and embedding fine-tuning, novel agentic workflows, advanced RAG and semantic search — using Python on Google Cloud (Vertex AI), LangChain/LlamaIndex, and vector search (Vertex AI Vector Search, Pinecone, pgvector). • Engineer for production: Design for latency, reliability, cost, and scale from day one; apply MLOps discipline so systems are served efficiently, monitored, and continuously improved — and actually reach production, where most AI work stalls. • Lead multi-step reasoning at scale: Architect and operate agentic workflows that automate complex reasoning reliably, with the design and verification discipline that keeps multi-agent systems from cascading into failure. • Advise clients and shape deals: Work directly with client leadership to understand strategy, propose state-of-the-art approaches, and shape solutions in pre-sales — the technical authority in the room. • Multiply the team: Elevate senior and mid-level engineers through architecture reviews, mentorship, and setting a high, teachable bar for AI-augmented engineering. • ## Your Technical Toolkit: • Core Languages: Mastery of Python and shell scripting; fluency across the modern AI engineering stack. • AI/LLM Ecosystem: Deep, current expertise with Google Gemini, GPT-class, and open models (LLaMA); advanced prompt engineering, fine-tuning, and evaluation. • Agentic Systems: Proven experience designing and productionizing agentic and multi-step reasoning systems (MCP, tool use, orchestration) — not just prototypes. • Data & Search: Expertise in vector databases (Vertex AI Vector Search, pgvector, Pinecone) and semantic search at production scale. • Infrastructure: Deep hands-on experience with Google Cloud / Vertex AI and architecting scalable, resilient software systems. • Frameworks: Strong command of LangChain, LlamaIndex, or equivalent orchestration layers — and the judgment to know when not to reach for them. • Engineering foundation: A first-class software engineer — clean, maintainable code, full SDLC ownership, and the architectural judgment to lead others.
Benefits
• This role is eligible for our competitive salary and comprehensive benefits package to support your well-being: • Comprehensive Health Insurance • Paid Leave (Vacation/PTO) • Paid Holidays • Parental Leave • Bereavement Leave • 401 (k) Employer Match • Employee Referral Bonuses • Check out our complete list of benefits here - >https://egen.ai/people/#benefits • Important: All roles are subject to standard hiring verification practices, which may include background checks, employment verification, and other relevant checks. • EEO and Accommodations:
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