AI/ML developer-AI Agent Engineer

TexcelVision Inc.
Austin, United States of America
1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Austin, United States of America

Tech stack

API
Artificial Intelligence
Azure
Python
Machine Learning
Software Deployment
Systems Integration
Large Language Models
Multi-Agent Systems
Generative AI
Web Filtering
Scikit Learn
HuggingFace
Virtual Agents

Job description

Researching, designing, implementing and managing software programs. Testing and evaluating new programs. Working closely with other developers, UX designers, business and systems analysts. AI Agent Engineer Designs and develops AI-driven agentic solutions, including autonomous workflows and Retrieval-Augmented Generation (RAG) systems, to enhance productivity, automate processes, and support intelligent decision-making with a focus on governance, security, and cost efficiency.

Requirements

Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity. Years Required/Preferred Experience 4 Required experience in AI/ML engineering or advanced data science 4 Required Proven track record of building and deploying production-grade autonomous agents. 4 Required Strong experience in context engineering 4 Required Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT. 4 Required Experience implementing RAG architectures using vector databases 4 Required Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI) 4 Required Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation 4 Required Experience implementing and extending the Model Context Protocol (MCP) to provide LLMs with secure, standardized access to local and remote data sources Experience implementing AI guardrails, content filtering, and safety controls 4 Required Understanding of data privacy and handling of sensitive data (PII/PHI) 2 Preferred Experience building multi-agent or autonomous agentic workflows 2 Preferred Experience optimizing LLM cost, token usage, and performance 2 Preferred Familiarity with enterprise AI deployment patterns and scalability considerations

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