Job description

ABOUT ARTIAN Artian AI is building agentic AI automation for financial services. Our platform enables reliable, autonomous AI agents to execute business-critical workflows across regulated enterprise environments. We are an in-person team in New York, building at the intersection of AI, enterprise software, workflow automation, and financial services. We move with urgency, take ownership, communicate transparently, and care deeply about doing excellent work. We are looking for people who are grounded under pressure, learn quickly, earn trust with teammates and customers, and want to help define how AI agents are deployed safely and effectively in the enterprise. About the Role Artian AI is looking for a Software Engineer - AI/ML to help build the intelligence layer of our agentic AI platform for financial services. You will work on the systems that enable AI agents to understand complex workflows, reason over enterprise data, interact with tools, and complete business-critical tasks reliably. This role is ideal for an engineer who has strong software fundamentals, applied machine learning experience, and a practical orientation toward shipping production systems. You should be excited by the challenge of turning fast-moving AI capabilities into dependable software used by financial institutions. WHAT YOU’LL DO - Build and improve AI/ML components that power autonomous enterprise workflows. - Work with large language models, embeddings, retrieval systems, classifiers, ranking systems, and agentic workflow architectures. - Develop evaluation frameworks to measure agent performance, accuracy, reliability, latency, and failure modes. - Prototype new AI capabilities and productionize the ones that create customer value. - Collaborate with backend, product, and solutions engineering to integrate AI capabilities into end-to-end workflows. - Design systems for observability, debugging, and continuous improvement of AI agents in production. - Stay current with developments in applied AI and bring a pragmatic lens to which techniques should be used in enterprise environments. WHAT WE’RE LOOKING FOR - Strong Python engineering skills and experience building production software. - Experience with applied machine learning, LLMs, NLP, embeddings, retrieval, ranking, or agentic systems. - Familiarity with ML tooling such as PyTorch, scikit-learn, vector databases, model evaluation frameworks, or data pipelines. - Ability to reason from first principles about model behavior, failure modes, latency, accuracy, and reliability. - Comfort working in ambiguity and quickly turning prototypes into robust software. - Strong communication skills and a bias toward ownership. NICE TO HAVE - BS in Computer Science, AI/ML, or a closely related technical field, or equivalent industry experience. - Experience building LLM-powered products, agent frameworks, or retrieval-augmented generation systems. - Experience with financial services, regulated workflows, compliance, auditability, or enterprise data environments. - Experience designing AI evaluations, human-in-the-loop systems, or production monitoring for ML systems. - Experience at an early-stage startup or in a high-ownership engineering environment. WHY JOIN ARTIAN - Build applied AI systems for real enterprise use cases, not demos. - Work on hard problems in reliability, automation, financial services, and AI governance. - Join an in-person team with high ownership and direct customer impact. - Help define how autonomous agents operate in regulated enterprise environments.

Requirements

Must-haves

Build and improve AI/ML components that power autonomous enterprise workflows.
Work with large language models, embeddings, retrieval systems, classifiers, ranking systems, and agentic workflow architectures.
Develop evaluation frameworks to measure agent performance, accuracy, reliability, latency, and failure modes.
Prototype new AI capabilities and productionize the ones that create customer value.
Collaborate with backend, product, and solutions engineering to integrate AI capabilities into end-to-end workflows.
Design systems for observability, debugging, and continuous improvement of AI agents in production.
Stay current with developments in applied AI and bring a pragmatic lens to which techniques should be used in enterprise environments.
Strong Python engineering skills and experience building production software.
Experience with applied machine learning, LLMs, NLP, embeddings, retrieval, ranking, or agentic systems.
Familiarity with ML tooling such as PyTorch, scikit-learn, vector databases, model evaluation frameworks, or data pipelines.
Ability to reason from first principles about model behavior, failure modes, latency, accuracy, and reliability.
Comfort working in ambiguity and quickly turning prototypes into robust software.
Strong communication skills and a bias toward ownership.
Build applied AI systems for real enterprise use cases, not demos.
Work on hard problems in reliability, automation, financial services, and AI governance.
Join an in-person team with high ownership and direct customer impact.
Help define how autonomous agents operate in regulated enterprise environments.

Nice-to-haves

BS in Computer Science, AI/ML, or a closely related technical field, or equivalent industry experience.
Experience building LLM-powered products, agent frameworks, or retrieval-augmented generation systems.
Experience with financial services, regulated workflows, compliance, auditability, or enterprise data environments.
Experience designing AI evaluations, human-in-the-loop systems, or production monitoring for ML systems.
Experience at an early-stage startup or in a high-ownership engineering environment.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlmachine learningdesign systemspythonllm

Platform: ashby
Effort: quick