Software Developer 2
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Job Location:
Austin, TX - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Job Summary:
The Software Developer will be responsible for building and deploying production-grade autonomous agents with a strong focus on context engineering and implementing Retrieval-Augmented Generation (RAG) architectures. This role requires deep expertise in LangChain LangGraph CrewAI or AutoGPT and proficiency in Python and AI/ML libraries. The developer will also implement and extend the Model Context Protocol (MCP) and AI guardrails ensuring data privacy and security.
The Software Developer will be responsible for building and deploying production-grade autonomous agents with a strong focus on context engineering and implementing Retrieval-Augmented Generation (RAG) architectures. This role requires deep expertise in LangChain LangGraph CrewAI or AutoGPT and proficiency in Python and AI/ML libraries. The developer will also implement and extend the Model Context Protocol (MCP) and AI guardrails ensuring data privacy and security.
Location:Austin Texas United States
Responsibilities:
- Building and deploying production-grade autonomous agents.
- Implementing RAG architectures using vector databases.
- Integrating LLMs via APIs.
- Implementing and extending the Model Context Protocol (MCP).
- Implementing AI guardrails content filtering and safety controls.
- Building and deploying production-grade autonomous agents.
- Implementing RAG architectures using vector databases.
- Integrating LLMs via APIs.
- Implementing and extending the Model Context Protocol (MCP).
- Implementing AI guardrails content filtering and safety controls.
Required Skills & Certifications:
- 4 years of experience in AI/ML engineering or advanced data science.
- 4 years of proven track record of building and deploying production-grade autonomous agents.
- 4 years of strong experience in context engineering.
- 4 years of deep experience with LangChain LangGraph CrewAI or AutoGPT.
- 4 years of experience implementing RAG architectures using vector databases.
- 4 years of proficiency in Python and AI/ML libraries (OpenAI Hugging Face Azure AI).
- 4 years of experience integrating LLMs via APIs.
- 4 years of knowledge of AI governance model lifecycle management and evaluation.
- 4 years of experience implementing and extending the Model Context Protocol (MCP) to provide LLMs with secure standardized access to local and remote data sources.
- 4 years of experience implementing AI guardrails content filtering and safety controls.
- 4 years of understanding of data privacy and handling of sensitive data (PII/PHI).
- 4 years of experience in AI/ML engineering or advanced data science.
- 4 years of proven track record of building and deploying production-grade autonomous agents.
- 4 years of strong experience in context engineering.
- 4 years of deep experience with LangChain LangGraph CrewAI or AutoGPT.
- 4 years of experience implementing RAG architectures using vector databases.
- 4 years of proficiency in Python and AI/ML libraries (OpenAI Hugging Face Azure AI).
- 4 years of experience integrating LLMs via APIs.
- 4 years of knowledge of AI governance model lifecycle management and evaluation.
- 4 years of experience implementing and extending the Model Context Protocol (MCP) to provide LLMs with secure standardized access to local and remote data sources.
- 4 years of experience implementing AI guardrails content filtering and safety controls.
- 4 years of understanding of data privacy and handling of sensitive data (PII/PHI).
Preferred Skills & Certifications:
- 2 years of experience building multi-agent or autonomous agentic workflows.
- 2 years of experience optimizing LLM cost token usage and performance.
- 2 years of familiarity with enterprise AI deployment patterns and scalability considerations.
- 2 years of experience building multi-agent or autonomous agentic workflows.
- 2 years of experience optimizing LLM cost token usage and performance.
- 2 years of familiarity with enterprise AI deployment patterns and scalability considerations.
Special Considerations:
- N/A
- N/A
Scheduling:
- N/A
- N/A
