We are working with an exciting client at the forefront of innovation in the intelligence operating system space. They are transforming how organizations deliver large-scale change by addressing the challenges of project complexity, delays, and cost overruns!

Do you have the skills to fill this role Read the complete details below, and make your application today.

Role Overview

As aSenior AI Solutions Engineer, you will design, develop, and deploy advancedAI agentic workflowsusing modernAI orchestration frameworkswhile applying expertise inretrieval-augmented generation (RAG)techniques, includingGraphRAG, andprompt engineering. You will build, fine-tune, and optimiselarge language models (LLMs)andtraditional ML modelsto address complex enterprise challenges.

This role requires a strong background insoftware engineering, ensuring that AI solutions are seamlessly integrated into production-grade systems with robust, scalable architectures. You will support a small team ofAI engineers, providing technical guidance and hands-on support while driving innovation and delivery.

Key Responsibilities

• Design and Orchestrate AI Agents: Build and deploy agentic AI workflows using modernAI orchestration frameworksto automate multi-step decision-making tasks.
• Implement Advanced RAG Techniques: Develop and optimiseretrieval-augmented generation (RAG)solutions, includingGraphRAG, to deliver grounded, real-time insights.
• Fine-Tune and Optimise LLMs: Fine-tune pre-trained transformer models using techniques likeLoRA, QLoRA, or similar methods, ensuring alignment with enterprise-specific use cases.
• Develop and Deploy ML Models: Build and operationalise traditional machine learning models for predictive analytics, trend detection, and automation workflows.
• Apply Advanced Prompt Engineering: Design and optimise prompts to enhance LLM performance, ensuring high-quality outputs tailored to enterprise programme tasks.
• Ensure Software Engineering Excellence: Build production-grade systems with robust, scalable architectures, adhering to software engineering best practices for clean code, testing, and deployment.
• Optimise Model Performance: Improve inference efficiency, reduce latency, and ensure seamless deployment of AI systems in production environments.
• Implement MLOps Pipelines: Develop automated workflows for training, deployment, and monitoring using tools likeMLflow,Kubeflow, or Azure ML to ensure operational reliability.
• Experiment and Evaluate: Develop frameworks for rigorous experimentation, model evaluation, and performance validation on real-world datasets.
• Support and Guide: Manage a small team ofAI engineers, providing technical guidance, conducting code reviews, and enabling the delivery of high-quality solutions.
• Collaborate Across Teams: Work closely with team members to ensure clean, structured data pipelines for ML workflows and partner withResearch Engineersto align outputs with knowledge base systems and enterprise requirements.
• Drive Innovation: Explore and integrate the latest advancements inAI orchestration frameworks, LLMs, and RAG techniques to ensure Pathfinder’s platform remains cutting edge.

What We're Looking For

Core Expertise:

• AI Agentic Workflows: Proven experience designing and deploying AI agents using modernAI orchestration frameworksto automate multi-step workflows.
• Retrieval-Augmented Generation (RAG): Deep expertise in RAG techniques, includingGraphRAG, embedding-based retrieval, and knowledge integration workflows.
• Prompt Engineering: Demonstrated experience optimising prompts to guide LLM behaviour and outputs for real-world applications.
• Fine-Tuning and ML Development: Strong experience fine-tuning LLMs and building traditional ML models for predictive analytics and automation.

Software Engineering Excellence:

• Strong background insoftware engineering, including experience with clean code principles, testing, version control, and scalable system design.
• Proven ability to integrate AI solutions into production-grade architectures with robust performance and maintainability.

Production AI & MLOps:

• Track record of deploying production-grade AI systems with a focus on reliability, scalability, and performance.
• Hands-on experience with MLOps tools likeMLflow,Kubeflow, or Azure ML to automate model deployment and lifecycle management.

Technical Skills:

• Programming: Advanced proficiency in Python and libraries like PyTorch, Hugging Face Transformers, TensorFlow, Numpy, and Pandas.
• Optimisation: Expertise in inference optimisation techniques (quantisation, distillation) and model-serving frameworks.
• Cloud Platforms: Experience deploying AI solutions onAzure(preferred) or other cloud platforms like AWS or GCP.

Collaboration & Leadership:

• Ability to guide a small team ofAI engineersthrough technical challenges while delivering hands-on contributions.
• Strong collaboration with cross-functional teams, including Research Engineers, to align outputs with knowledge base systems and business needs.

Mindset & Approach

• Software-Driven Engineer: Balances AI expertise with a commitment to strong software engineering principles and best practices.
• Innovative Problem Solver: Combines AI agents, RAG, and ML models to design real-world, impactful solutions.
• Production-Focused: Delivers reliable, scalable, and efficient AI systems ready for deployment.
• Continuous Learner: Stays ahead of advancements in AI, orchestration frameworks, and engineering techniques.

What Success Looks Like

Success in this role will be measured by:

• Design, deployment, and optimisation ofAI agentic workflowsusing modern orchestration frameworks.
• Development of scalable, production-grade solutions leveragingRAG techniques,fine-tuned LLMs, andtraditional ML models.
• Integration of AI systems into robust, maintainable software architectures.
• Building reliable MLOps pipelines for seamless deployment, monitoring, and optimisation.
• Effective technical management of a small team ofAI engineersto deliver high-quality results.

What We Offer

• Competitive salary
• Bonus scheme
• Wellness allowance
• Fully remote working (with regular company get-togethers)
• Private medical and dental insurance*
• Life assurance, critical illness cover, and income protection*

Provision and availability depend on your country of residence – we’ll discuss this with you.

Join to lead the design and orchestration of AI agentic systems, advanced RAG techniques, and software-driven AI workflows that power enterprise programme management solutions.