AI Engineer (Production Agentic AI)
CrooterAbout the role
AI Engineer (Production Agentic AI)
Location: New York (Onsite) (or update if applicable)
Compensation: $200,000–$250,000 Base + Equity + Benefits
About the Role
We're looking for a highly technical AI Engineer who has successfully built and shipped production-grade AI products powered by Large Language Models (LLMs). This role requires someone who can own AI features from concept to deployment, building reliable, scalable, and user-facing AI systems.
You'll work on designing intelligent agent workflows, building robust evaluation pipelines, and shipping AI capabilities that directly impact customers.
What You'll Do
Design, build, and deploy production-grade AI agents using modern LLM frameworks.
Own AI features end-to-end, from architecture and prototyping through production deployment and iteration.
Build multi-agent workflows with planning, orchestration, memory, and tool integrations.
Develop scalable Retrieval-Augmented Generation (RAG) systems using vector databases and embeddings.
Implement LLM evaluation frameworks to measure quality, accuracy, safety, and reliability.
Collaborate closely with product and engineering teams to rapidly ship customer-facing AI capabilities.
Optimize latency, reliability, observability, and cost of production AI systems.
Continuously improve AI products through experimentation, monitoring, and user feedback.
Required Qualifications
3–8 years of professional software engineering experience.
Strong production experience with Python.
Experience building and deploying production LLM applications.
Hands-on experience with LangGraph or similar AI orchestration frameworks.
Experience implementing:
Multi-agent workflows
Tool calling
Structured outputs
Agent orchestration
Context and memory management
Experience building production RAG systems using vector databases (Pinecone, Weaviate, pgvector, FAISS, ChromaDB, etc.).
Experience with FastAPI, REST APIs, Docker, and cloud platforms (AWS/GCP/Azure).
Strong understanding of scalable backend systems and production deployment.
Preferred Qualifications
Experience building 0→1 AI products from concept to production.
Experience working in a startup or fast-paced product environment.
Experience collaborating directly with founders or product leadership.
Experience shipping customer-facing AI products with measurable business impact.
Familiarity with:
CrewAI
AutoGen
MCP (Model Context Protocol)
LangSmith
RAGAS
OpenAI, Anthropic, Gemini, or other frontier LLMs
Bachelor's degree in Computer Science or a related technical field.
Nice to Have
Fine-tuning LLMs
AI observability and monitoring
LLM safety and guardrails
Prompt engineering and optimization
AI evaluation pipelines and regression testing
Kubernetes and production MLOps
Please Highlight in Your Application
To help us evaluate your experience, please include:
A production AI agent or AI product you've built.
Your specific role in taking it from concept to production.
AI orchestration framework(s) used (e.g., LangGraph, CrewAI).
LLM evaluation methods or frameworks you've implemented.
Scale of the system (users, requests/day, customers, etc.).
Startup or founding experience (if applicable).
Ideal Candidate
We're looking for someone who has built production AI systems, not just prototypes. The strongest candidates will have experience shipping reliable, customer-facing AI products, taking ownership from idea through deployment, and working in fast-moving engineering environments where product impact is a priority.
More information
Minimum education level
Bachelor's
Experience level
Mid-level (3-4 years)
Job skills
Machine Learning
Deep Learning
Natural Language Processing
Model Deployment
Data Analysis
Python Programming
Neural Networks
AI Ethics
Certifications
0-1 product building
Responsibilities
- Design, build, and deploy production-grade AI agents using modern LLM frameworks.
- Own AI features end-to-end, from architecture and prototyping through production deployment and iteration.
- Build multi-agent workflows with planning, orchestration, memory, and tool integrations.
- Develop scalable Retrieval-Augmented Generation (RAG) systems using vector databases and embeddings.
- Implement LLM evaluation frameworks to measure quality, accuracy, safety, and reliability.
- Collaborate closely with product and engineering teams to rapidly ship customer-facing AI capabilities.
- Optimize latency, reliability, observability, and cost of production AI systems.
- Continuously improve AI products through experimentation, monitoring, and user feedback.
Qualifications
- 3–8 years of professional software engineering experience.
- Strong production experience with Python.
- Experience building and deploying production LLM applications.
- Hands-on experience with LangGraph or similar AI orchestration frameworks.
- Experience implementing multi-agent workflows, tool calling, structured outputs, agent orchestration, context and memory management.
- Experience building production RAG systems using vector databases.
- Experience with FastAPI, REST APIs, Docker, and cloud platforms (AWS/GCP/Azure).
- Strong understanding of scalable backend systems and production deployment.
Benefits
- Equity
- Benefits
Skills mentioned
About Crooter
Crooter is an executive search partner for high growth, venture backed software companies, building the teams behind tomorrow's most ambitious businesses, from founding hires through pre-IPO leadership. We partner with founders, executive teams, and hiring leaders to identify and secure exceptional talent across every function that drives growth, including go to market, engineering, product, design, customer success, operations, executive leadership, and the C suite. Our clients span the software economy, with particular expertise across AI and machine learning, cloud infrastructure, enterprise software, developer tools, cybersecurity, data and analytics, fintech, healthtech, and other high growth technology sectors. Every search begins with a strategic hiring brief, not a job advertisement. We don't rely on job boards or high volume outreach. Instead, we headhunt directly, engaging exceptional professionals who are already succeeding in their roles, not simply those actively searching for their next opportunity. Before approaching the market, we work closely with our clients to define the role, align on success criteria, benchmark compensation, and build a clear hiring strategy. This ensures every search starts with clarity, precision, and a shared understanding of what outstanding looks like. We believe great hiring is never transactional. Every search is bespoke, built around the company, its stage of growth, its culture, and the impact the successful hire will make. Our approach combines speed with quality, market intelligence with rigorous assessment, and long term partnerships over short term placements. The result is a recruitment process that delivers exceptional people who create lasting impact. No templates. No scripts. No shortcuts. Just world class executive search for ambitious software companies. 📍 Executive Search | Software | Venture Backed Companies 🤝 Trusted by founders, executives, and hiring leaders 🚀 Building exceptional teams from