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Staff AI Engineer
CloudTara Technologies
5 hours ago
Full-time
On-site
New York City, New York, United States
We’re looking for a Staff AI Engineer to set the technical direction for how we build, ship, and scale AI-powered products. You’ll be a hands‑on technical leader who takes ambiguous, high‑impact problems from research prototype to reliable production systems, and who raises the bar for the engineers around you.
What You’ll Do
Own the architecture and technical strategy for our core AI systems, including LLM applications, retrieval, agents, and evaluation infrastructure Design and ship production‑grade AI features that are fast, reliable, cost‑efficient, and measurable Build rigorous evaluation frameworks (offline and online) so we can ship model and prompt changes with confidence Make build‑vs‑buy and model selection decisions across foundation models, fine‑tuned models, and open‑source options Partner with Product, Design, and Data teams to turn business problems into well‑scoped AI solutions Mentor engineers in the team, lead design reviews, and drive engineering best practices across teams Establish standards for AI safety, observability, privacy, and responsible deployment Stay close to the frontier of AI research and tooling, and pragmatically bring what works into our stack What We’re Looking For
8+ years of software engineering experience, with 3+ years building and shipping ML/AI systems in production Deep hands‑on experience with LLMs: prompt engineering, RAG, fine‑tuning, tool use/agents, and evaluation Strong programming skills in Python (plus TypeScript/Go/Java is a bonus) and solid software design fundamentals Experience designing scalable, distributed systems and ML infrastructure (serving, latency optimization, cost control) Familiarity with the modern AI stack: vector databases, orchestration frameworks, MLOps tooling, and cloud platforms (AWS/GCP/Azure) A track record of technical leadership across teams, including influencing roadmaps without relying on authority Excellent communication skills, able to explain complex tradeoffs to both engineers and executives Nice to Have
Experience with multi‑agent systems, model distillation, or on‑device/edge inference Contributions to open‑source AI projects, publications, or conference talks Background in FinTech Experience building AI products from 0 to 1 in a startup environment
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Own the architecture and technical strategy for our core AI systems, including LLM applications, retrieval, agents, and evaluation infrastructure Design and ship production‑grade AI features that are fast, reliable, cost‑efficient, and measurable Build rigorous evaluation frameworks (offline and online) so we can ship model and prompt changes with confidence Make build‑vs‑buy and model selection decisions across foundation models, fine‑tuned models, and open‑source options Partner with Product, Design, and Data teams to turn business problems into well‑scoped AI solutions Mentor engineers in the team, lead design reviews, and drive engineering best practices across teams Establish standards for AI safety, observability, privacy, and responsible deployment Stay close to the frontier of AI research and tooling, and pragmatically bring what works into our stack What We’re Looking For
8+ years of software engineering experience, with 3+ years building and shipping ML/AI systems in production Deep hands‑on experience with LLMs: prompt engineering, RAG, fine‑tuning, tool use/agents, and evaluation Strong programming skills in Python (plus TypeScript/Go/Java is a bonus) and solid software design fundamentals Experience designing scalable, distributed systems and ML infrastructure (serving, latency optimization, cost control) Familiarity with the modern AI stack: vector databases, orchestration frameworks, MLOps tooling, and cloud platforms (AWS/GCP/Azure) A track record of technical leadership across teams, including influencing roadmaps without relying on authority Excellent communication skills, able to explain complex tradeoffs to both engineers and executives Nice to Have
Experience with multi‑agent systems, model distillation, or on‑device/edge inference Contributions to open‑source AI projects, publications, or conference talks Background in FinTech Experience building AI products from 0 to 1 in a startup environment
#J-18808-Ljbffr