AI Engineer/Architect

Empiric; Indianapolis (IN); On-site; USD 100,000 - 150,000; Full time

Job summary

A tech solutions provider is seeking a highly skilled software engineer with expertise in building AI-native applications. This role involves designing and optimizing workflows, collaborating with multidisciplinary teams, and utilizing modern development tools. Candidates should have over 5 years of experience in software engineering, with a strong focus on AI technologies. The ideal candidate will excel in full-stack development across various technologies, including React and Python, while managing cloud-native systems. This is a unique opportunity to shape the future of AI applications while ensuring robust engineering principles are at the forefront.

Qualifications

• 5+ years of professional software engineering experience, including at least 2 years building AI-powered systems.
• Strong background in full-stack technologies and modern front-end frameworks.
• Familiarity with AI and LLM development tools.

Responsibilities

• Design, prototype, and scale AI-native applications and agent-based systems.
• Optimize LLM-driven workflows with retrieval-augmented generation techniques.
• Partner with teams to translate experimentation into production-ready features.

Skills

Software engineering

AI-powered systems

Full-stack development

React

TypeScript

Python

Node.js

Go

SQL

NoSQL

Cloud-native architectures

Kubernetes

Docker

CI/CD workflows

Monitoring

Tools

Cursor

Claude Code

GitHub Copilot

LangChain

CrewAI

Job description

Our customer design and deliver bespoke AI solutions that combine state-of-the-art models with robust, production-grade engineering. We don’t believe AI is magic—but when it’s built thoughtfully and executed well, it can feel that way. We’re seeking a hands‑on builder who is excited to push the boundaries of what AI can do, while grounding innovation in strong full‑stack engineering principles.

What You’ll Do

• Design, prototype, and scale AI‑native applications and agent‑based systems that drive real business outcomes.
• Work end‑to‑end across the stack, including front‑end development (React, TypeScript), backend services (Python, Node.js, Go), APIs, and data stores (SQL, NoSQL, and vector databases).
• Build and optimize LLM‑driven workflows, leveraging techniques such as retrieval‑augmented generation (RAG), embeddings, multi‑agent orchestration, and effective context management.
• Architect, deploy, and maintain infrastructure, including CI/CD pipelines, Kubernetes, cloud services, and observability tooling.
• Move efficiently from proof‑of‑concept to production, balancing speed with scalability, security, and long‑term maintainability.
• Continuously optimize AI systems for accuracy, performance, latency, and cost efficiency.
• Partner closely with customers, engineers, product managers, and designers to translate experimentation into reliable, production‑ready features.
• Stay hands‑on with modern, developer‑first tools such as Cursor, Claude Code, GitHub Copilot, and similar platforms to maximize productivity.

About You

• 5+ years of professional software engineering experience, including at least 2 years building AI‑powered systems.
• Strong full‑stack background, with experience in modern front‑end frameworks (React, TypeScript), backend development (Python, Node.js, Go), and a range of databases (SQL, NoSQL, vector stores).
• Familiarity with AI and LLM development tools such as Cursor, Claude Code, GitHub Copilot, LangChain, CrewAI, or comparable frameworks.
• Hands‑on experience with cloud‑native architectures (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD workflows, monitoring, and scalable systems.
• Solid understanding of the LLM lifecycle, including prompting strategies, evaluation, fine‑tuning, embeddings, RAG, and agent design.
• A pragmatic engineering mindset—you recognize that reliable AI systems require testing, observability, safeguards, and fallback logic, not just clever prompts.
• Strong communication and collaboration skills, with the ability to bridge technical depth and business context.
• Curiosity and enthusiasm for exploring new ideas, paired with a commitment to delivering production‑quality software.