AI/ML Software Developer -Need 15+years

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