ML & Agentic Solutions Engineer

Provoke Solutions·Remote(New Zealand)
Sales

WFA Digital Insight

The demand for AI and machine learning specialists has skyrocketed, with a 27% increase in job postings over the past year. Provoke Solutions is at the forefront of this trend, and their ML & Agentic Solutions Engineer role is an exciting opportunity for those who want to shape the future of conversational AI. With the remote work landscape continuing to evolve, this role offers the chance to work with a global team and collaborate on cutting-edge projects. Before applying, candidates should be prepared to showcase their skills in building AI systems, as well as their ability to communicate complex technical ideas to non-technical audiences.

Job Description

About the Role

The ML & Agentic Solutions Engineer role at Provoke Solutions is a unique opportunity to work at the intersection of engineering, product thinking, and creative problem-solving. As a member of the team, you will be responsible for designing and building next-generation conversational and agentic experiences that reason, plan, act, and collaborate with humans across tools, systems, and real business environments. This role is ideal for someone who is passionate about building AI systems and wants to be at the forefront of the latest developments in LLMs and conversational interfaces.

The role is based in New Zealand, but you will be working with a global team, collaborating with colleagues across NZ, Australia, and the US. This is a remote role, offering the flexibility to work from anywhere, and you will be expected to be self-motivated and disciplined in your work.

As an ML & Agentic Solutions Engineer, you will be working on a wide range of projects, from designing conversational AI agents to implementing MCP servers and integrating them with enterprise systems. You will be expected to be bright, curious, and capable, with a strong ability to communicate complex technical ideas to non-technical audiences.

What You Will Do

  • Design conversational AI agents using LLMs, RAG patterns, fine-tuned dialogue models, and modern prompting techniques
  • Build agentic and multi-agent solutions using frameworks like OpenAI Agents SDK, LangGraph, and PydanticAI
  • Implement MCP servers using tools like FastMCP and integrate them with enterprise systems
  • Connect LLM-based agents with REST APIs, databases, internal tools, and external SaaS platforms
  • Create human-in-the-loop collaboration flows alongside UX, product, and data teams
  • Apply agent orchestration, decision logic, memory management, and context routing for robust multi-step experiences
  • Experiment, test, refine, and push the boundaries of what tool-using LLMs can do
  • Collaborate with cross-functional teams to design and implement conversational AI solutions
  • Participate in code reviews and contribute to the improvement of the codebase
  • Stay up-to-date with the latest developments in LLMs and conversational interfaces

What We Are Looking For

  • Hands-on capability in building Conversational AI agents
  • Experience implementing LLM-powered systems using RAG, fine-tuning, or structured prompting
  • Practical familiarity with agent frameworks like OpenAI Agents SDK, LangGraph, PydanticAI, or similar
  • Experience implementing custom MCP servers or integrating with MCP-compatible tools
  • Confidence connecting agents with APIs, SQL databases, internal tools, or enterprise systems
  • Ability to design fallback logic, memory strategies, and multi-step reasoning flows
  • Strong abstract thinking and the ability to break ambiguous problems into solvable components
  • Experience with chatbots, virtual assistants, or conversational UX
  • Familiarity with tool use, sub-agent delegation, planning, and memory patterns

Nice to Have

  • Two to three years of building AI or ML systems
  • Experience integrating APIs or working across web, chat, or voice modalities
  • Awareness of data privacy, user consent, and ethical AI considerations
  • Experience with cloud-based platforms and containerization
  • Knowledge of container orchestration tools like Docker or Kubernetes

Benefits and Perks

  • Competitive salary and benefits package
  • Opportunity to work on cutting-edge projects with a global team
  • Flexible working hours and remote work options
  • Professional development opportunities and training budget
  • Access to the latest tools and technologies
  • Collaborative and dynamic work environment
  • Recognition and reward for outstanding performance
  • Comprehensive health and wellness program
  • Generous parental leave policy

How to Stand Out

  • Be prepared to showcase your skills in building AI systems, including experience with LLMs and conversational interfaces.
  • Highlight your ability to communicate complex technical ideas to non-technical audiences.
  • Make sure to include examples of your previous work, such as chatbots or virtual assistants, in your portfolio.
  • Be prepared to discuss your approach to designing fallback logic, memory strategies, and multi-step reasoning flows.
  • Show enthusiasm for staying up-to-date with the latest developments in LLMs and conversational interfaces.
  • Emphasize your experience with cloud-based platforms and containerization.
  • Be prepared to discuss your experience with data privacy, user consent, and ethical AI considerations.

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