JV
AI/ML Software Developer -Need 15+years
Jobs via Dice
Austin · Hybrid Full-time Senior Today
About the role
Job Title
AI/ML Software Developer – RAG
Location
Austin, TX (Hybrid)
Work Type
Contract (C2C)
Experience Required
15+ Years (Senior Level Only)
Interview Mode
In-Person Only (No Exceptions)
Work Schedule
- Hybrid Role
- 3 Days Remote
- 2 Days Onsite (Monday & Thursday Mandatory)
Important Notes
- Only LOCAL candidates (Austin Metro Area)
- Out-of-state candidates NOT allowed
- Candidates must already be residing in Texas
- No relocation candidates
Job Summary
We are seeking a highly experienced AI/ML Software Developer specializing in Retrieval-Augmented Generation (RAG) and agentic AI systems. The candidate will design, develop, and deploy AI-driven autonomous solutions to improve productivity, automate workflows, and support intelligent decision-making with a strong focus on governance, security, and cost efficiency.
Key Responsibilities
- Design and develop AI-driven agentic workflows and autonomous systems
- Build and implement RAG architectures using vector databases
- Develop, test, and deploy scalable AI/ML solutions
- Collaborate with developers, UX designers, and business analysts
- Implement AI governance, safety controls, and content filtering
- Optimize LLM performance, token usage, and cost efficiency
- Ensure secure data handling (PII/PHI compliance)
- Integrate LLMs via APIs and enterprise systems
Required Skills
- Strong experience in AI/ML engineering or advanced data science
- Proven experience building production‑grade autonomous agents
- Expertise in context engineering
- Hands‑on experience with:
- LangChain
- LangGraph
- CrewAI
- AutoGPT
- Experience with RAG architectures & vector databases
- Strong Python programming skills
- Experience with AI/ML libraries:
- OpenAI
- Hugging Face
- Azure AI
- Experience integrating LLMs via APIs
- Knowledge of AI governance and model lifecycle management
- Experience implementing Model Context Protocol (MCP)
- Experience with AI guardrails and safety mechanisms
- Understanding of data privacy (PII/PHI)
- Experience in multi‑agent systems
- LLM optimization (cost, tokens, performance)
- Enterprise AI deployment & scalability knowledge
Nice to Have
- Experience in large‑scale enterprise AI implementations
- Strong understanding of secure AI system design
Requirements
- Strong experience in AI/ML engineering or advanced data science
- Proven experience building production-grade autonomous agents
- Expertise in context engineering
- Hands-on experience with LangChain
- Hands-on experience with LangGraph
- Hands-on experience with CrewAI
- Hands-on experience with AutoGPT
- Experience with RAG architectures & vector databases
- Strong Python programming skills
- Experience with AI/ML libraries: OpenAI
- Experience with AI/ML libraries: Hugging Face
- Experience with AI/ML libraries: Azure AI
- Experience integrating LLMs via APIs
- Knowledge of AI governance and model lifecycle management
- Experience implementing Model Context Protocol (MCP)
- Experience with AI guardrails and safety mechanisms
- Understanding of data privacy (PII/PHI)
- Experience in multi-agent systems
- LLM optimization (cost, tokens, performance)
- Enterprise AI deployment & scalability knowledge
Responsibilities
- Design and develop AI-driven agentic workflows and autonomous systems
- Build and implement RAG architectures using vector databases
- Develop, test, and deploy scalable AI/ML solutions
- Collaborate with developers, UX designers, and business analysts
- Implement AI governance, safety controls, and content filtering
- Optimize LLM performance, token usage, and cost efficiency
- Ensure secure data handling (PII/PHI compliance)
- Integrate LLMs via APIs and enterprise systems
Skills
AIAI governanceAI guardrailsAI/MLAutoGPTAzure AICrewAIHugging FaceLangChainLangGraphLLMMLModel Context Protocol (MCP)OpenAIPythonRAGVector databases
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