AI Engineer

ReqRoute,Inc; Town of Texas (WI); Remote; USD 100,000 - 160,000; Full time

Benefits offered by this job

Remote work

Job summary

ReqRoute,Inc seeks an AI Engineer to work remotely with client domain teams to identify high-value AI opportunities and validate feasibility before solutioning.

You will design, build, and deploy AI agents using agentic frameworks, with memory, structured outputs, and error recovery. The role emphasizes RAG pipelines and enterprise integration.

Qualifications

• Master's degree in CS/AI/DS or related field.
• PhD preferred for advanced research.
• Strong Python production-grade skills.
• Hands-on with LLMs, prompts, and tool use.
• Experience building RAG pipelines and memory architectures.

Responsibilities

• Embed with client domain teams to identify high-value AI opportunities and validate feasibility.
• Design, build, and deploy AI agents using agentic frameworks with tool use and memory.
• Build RAG pipelines grounded in client data and memory architectures.
• Integrate AI with client systems via APIs and gateways with robust error handling.
• Define success metrics, run benchmarks, and monitor deployed AI systems.
• Partner with client teams, run workshops, and enable AI adoption on the ground.
• Surface gaps and requests to improve reusable offerings.

Skills

Python programming

LLMs

Prompt engineering

Agentic workflows

Problem solving

Communication

Education

Master's degree in Computer Science or AI/DS

PhD preferred

Tools

LangGraph

LangChain

CrewAI

Google ADK

REST APIs

AWS / Azure / GCP

Git

Docker

Job description

AI Engineer
Remote

JD:

• Embed with client domain teams to identify high-value AI opportunities, map pain points to platform capabilities, and validate feasibility before solutioning.
• Design, build, and deploy AI agents using agentic frameworks (LangGraph, CrewAI, Google ADK) with tool use, memory, structured outputs, and error recovery.
• Build retrieval-augmented generation (RAG) pipelines grounded in client enterprise data - designing context engineering and memory architectures for multi-turn and multi-agent workflows.
• Integrate AI solutions with client enterprise systems via APIs, MCP tool gateways, CRM, billing, and operational platforms - handling authentication, rate limiting, and production-grade error handling.
• Define success metrics in partnership with client stakeholders, build evaluation harnesses, and establish continuous benchmarking and quality monitoring for deployed AI systems.
• Serve as a trusted technical partner to client teams - run workshops, pair-program with domain engineers, and drive AI adoption and enablement on the ground.
• Surface platform gaps, friction, and feature requests back to the AI architecture and engineering teams to improve reusable offerings.

Must Have's:

• 3-5 yrs experience
• Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field with 1 3 years of relevant experience. PhD preferred.
• Strong production-grade Python programming skills - not notebook-grade; experience building deployable, maintainable AI applications.
• Hands-on experience with LLMs (GPT, Claude, Gemini), prompt engineering, structured outputs, function calling, and agentic workflow design.
• Experience designing and deploying RAG pipelines - embeddings, vector databases, reranking, hybrid search, and retrieval optimization.
• Familiarity with agentic AI frameworks such as LangGraph, LangChain, CrewAI, Google ADK, or similar orchestration tools.
• Working knowledge of REST APIs, cloud platforms (AWS, Azure, or GCP), Git, Docker, and modern software development practices.
• Strong analytical, problem-solving, and communication skills with the ability to explain AI trade-offs to non-technical stakeholders.
• Consultative mindset - comfortable operating in ambiguous environments, discovering problems, and defining approaches independently.