AI Engineer (Applied AI Systems)

Experience: 35 years

Education: Bachelors in Computer Science, AI/ML, Data Science, Engineering, or a related

field

Location: Flexible / Hybrid

Employment Type: Full-time/ Consultant

Role Overview:

We are building agentic, domain-specific AI systems for complex, high-stakes decision

environments. We are hiring AI Engineer to design, build, and evolve end-to-end AI solutions- from early system architecture to deployable, client-ready implementations. In this role, you will work across the full lifecycle of AI systems: translating loosely defined problems into structured system designs, implementing applied ML and LLM-based workflows, and delivering reliable, explainable solutions that operate in real institutional

contexts.

This is a hands-on role with high ownership and accountability. You will help define how we

build AI - its system patterns, technical standards, and delivery philosophy- while working

closely with the founder to move solutions from concept to production.

Key Responsibilities

Design and build end-to-end AI systems using applied ML and LLMs

Translate ambiguous problem statements into clear system architectures

Implement agentic workflows including task orchestration, tool use, and memory

Build scoring, ranking, and decision logic that is auditable and explainable

Integrate structured and unstructured data (documents, text, transcripts, logs)

Deliver client-ready outputs such as dashboards, reports, and structured insights

Iterate rapidly based on feedback while maintaining system reliability

Collaborate closely with the founder on technical and architectural decisions

What This Role Is Not:

A research or academic ML role

A narrow data engineering position

A pure backend or infrastructure role

A role focused only on experimentation or demos

Required Experience & Skills:

35 years of experience as an AI Engineer, ML Engineer, or Applied ML Developer

Strong proficiency in Python and building data-driven systems

Hands-on experience with LLMs, embeddings, and RAG-based pipelines

Experience combining rules, heuristics, ML models, and LLM outputs

Ability to work with incomplete data and evolving requirements

Strong problem-solving skills and clear technical communication

Good to Have:

Experience building AI systems for enterprises or regulated environments

Familiarity with agent frameworks or workflow orchestration tools

Experience with dashboards, reporting layers, or insight delivery systems

Startup or early-stage product experience

Why Join us:

Be part of the founding technical core of the company

Build AI systems used by real decision-makers, not internal demos

Build architecture, standards, and engineering culture

Work directly with the founder on high-impact systems

Clear growth path into Lead AI Engineer as we scale

What We Value:

Ownership over titles

Speed with judgment

Practical systems over theoretical elegance

Responsibility, clarity, and execution

If you enjoy building AI systems that actually get deployed and used, this is the place