AI Engineer (Applied AI Systems)

Experience: 3–5 years

Education: Bachelor’s 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:

• 3–5 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