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AI Consultant - Foundry: AI / Data Solutions (Milton Keynes Hybrid)

Contract: Part-time to Full-time Transition

Location: Milton Keynes (1+ day per week on-site)

Duration: Initial 2–3 months, with potential for extension or permanent conversion

We are supporting a global AI and data consultancy in hiring a Client Success Engineer to work with enterprise clients implementing advanced AI and data-driven solutions. This position is ideal for someone who enjoys both the technical and relationship-building side of delivery, designing, prototyping, and deploying real-world solutions that deliver measurable business impact.

The Role

• On-site presence in Milton Keynes at least one day per week
• Work directly with enterprise clients to understand challenges and deliver AI and data solutions
• Experience with Palantir/Foundry suite
• Design and implement prototypes, proof-of-concepts, and production-ready systems
• Collaborate with Sales, Product, and Engineering teams to ensure delivery excellence
• Initial part-time engagement for November at two days per week and December at three days per week
• Potential to transition to full-time in the new year, with the option to move permanently

About You

• Background in data engineering, AI or software development
• Excellent communication and stakeholder engagement skill
• Proven ability to translate business problems into technical solutions
• Flexible, proactive, and confident managing multiple projects simultaneously

Senior AI Software Engineer

London

£90,000-£130,000

I’m partnering with a dynamic AI consultancy that embeds itself within client businesses, listening closely, then building bespoke agentic AI solutions that automate processes, improve speed, and enhance decision-making.

Role Responsibilities

As a Senior AI Applied Engineer, you will:

• Build & Deploy AI-Driven Software Solutions
• You’ll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation.
• Own Project-Based Work Across Diverse Domains
• You’ll tackle varied engagements, ranging in length and complexity, and support multiple clients.
• Ensure Scalable and Reliable Deployment
• Your role includes end-to-end responsibility for deploying AI solutions that are robust, maintainable, and optimized for performance at scale.
• Act as a Strong Team Contributor and Communicator
• While you won’t lead client engagements, you’ll work closely with clients and internal teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities.
• Leverage Generative AI Expertise
• Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery.

Who We're Looking For

Essential Qualifications & Experience

• Strong software engineering background with deep experience deploying scalable systems
• At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency
• Comfortable with project-based, delivery-focused work, even if no prior consultancy experience
• Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders
• Reliable, consistent work history; this is a long-term growth-focused opportunity within an expanding team

Ready to Apply?

If this resonates with your background and career path, let’s talk. Please share your CV highlighting your engineering experience and where generative AI has featured, especially in deployment or integration roles.

Job Title: AI Researcher

Location: Cambridge or London, UK

This is a permanent position with candidates required to do hybrid working in either Cambridge or London.

Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are safe, controllable, and capable of producing high-quality outputs across multiple modalities. You’ll sit at the intersection of RL, LLMs, and generative modelling, helping us build the next generation of foundation models

Responsibilities:

Develop and refine RLHF algorithms for large language and generative models.

Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment.

Train, fine-tune, and evaluate LLMs and diffusion models at scale.

Design experiments to align generative outputs with human and organisational preferences.

Collaborate with researchers, engineers, and human feedback teams to build scalable alignment pipelines.

Publish findings in top-tier AI conferences and contribute to open-source frameworks.

Key Requirements:

PhD in Computer Science, Machine Learning, or related field.

Publications at NeurIPS, ICML, ICLR, ACL, or related venues.

Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF).

Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs).

Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow).

Proficiency in Python and standard ML libraries.

Solid foundations in probability, optimisation, and statistics.

Experience working with large-scale distributed training on GPUs/TPUs.

If this sounds of interest, please reach out to

Job Title: AI Researcher

Location: Cambridge or London, UK

This is a permanent position with candidates required to do hybrid working in either Cambridge or London.

Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are safe, controllable, and capable of producing high-quality outputs across multiple modalities. You’ll sit at the intersection of RL, LLMs, and generative modelling, helping us build the next generation of foundation models

Responsibilities:

Develop and refine RLHF algorithms for large language and generative models.

Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment.

Train, fine-tune, and evaluate LLMs and diffusion models at scale.

Design experiments to align generative outputs with human and organisational preferences.

Collaborate with researchers, engineers, and human feedback teams to build scalable alignment pipelines.

Publish findings in top-tier AI conferences and contribute to open-source frameworks.

Key Requirements:

PhD in Computer Science, Machine Learning, or related field.

Publications at NeurIPS, ICML, ICLR, ACL, or related venues.

Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF).

Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs).

Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow).

Proficiency in Python and standard ML libraries.

Solid foundations in probability, optimisation, and statistics.

Experience working with large-scale distributed training on GPUs/TPUs.

If this sounds of interest, please reach out to

Senior AI Software Engineer

London

£90,000-£130,000

I’m partnering with a dynamic AI consultancy that embeds itself within client businesses, listening closely, then building bespoke agentic AI solutions that automate processes, improve speed, and enhance decision-making.

Role Responsibilities

As a Senior AI Applied Engineer, you will:

• Build & Deploy AI-Driven Software Solutions
• You’ll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation.
• Own Project-Based Work Across Diverse Domains
• You’ll tackle varied engagements, ranging in length and complexity, and support multiple clients.
• Ensure Scalable and Reliable Deployment
• Your role includes end-to-end responsibility for deploying AI solutions that are robust, maintainable, and optimized for performance at scale.
• Act as a Strong Team Contributor and Communicator
• While you won’t lead client engagements, you’ll work closely with clients and internal teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities.
• Leverage Generative AI Expertise
• Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery.

Who We're Looking For

Essential Qualifications & Experience

• Strong software engineering background with deep experience deploying scalable systems
• At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency
• Comfortable with project-based, delivery-focused work, even if no prior consultancy experience
• Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders
• Reliable, consistent work history; this is a long-term growth-focused opportunity within an expanding team

Ready to Apply?

If this resonates with your background and career path, let’s talk. Please share your CV highlighting your engineering experience and where generative AI has featured, especially in deployment or integration roles.

AI Engineer

Rate - £850

Hybrid working - London

What you'll do

• Design and build AI prototypes using LLMs, agentic workflows, and vector-based knowledge retrieval
• Collaborate with investment teams and data scientists to identify and scope high-impact use cases
• Implement and orchestrate multi-agent systems using frameworks such as LangGraph or similar tools
• Develop pipelines and interfaces for prompt engineering, context injection, and fine-tuned workflows
• Build internal demos and proof-of-concepts for investment research, market commentary, and portfolio analysis

The knowledge, experience and qualifications you need

• Strong proficiency in Python, particularly for AI/ML, data engineering, or automation use cases
• Experience working with or building applications around large language models (open-source or commercial)
• Familiarity with LLM agents, orchestration frameworks (e.g. LangGraph, LangChain), and context management
• Experience with cloud platforms (AWS preferred) and associated services for AI workloads
• A background in software engineering or data science, ideally in a research-driven or exploratory environment
• Strong collaboration skills and ability to work with investment stakeholders

The knowledge, experience and qualifications that will help

• Experience working with knowledge graphs or vector databases
• Experience working in an agile environment with rapid prototyping and iteration
• Exposure to front-end frameworks (e.g. React) is a nice-to-have but not required
• Interest in the evolving field of AI governance, accuracy, and explainability
• Understanding of investment data – an eagerness to learn is fine