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Forward Deployed Engineer; Python, AI​/ML, Generative AI

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Modus Create
Full Time position
Listed on 2026-09-04
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer, Machine Learning/ ML Engineer, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 90000 - 120000 GBP Yearly GBP 90000.00 120000.00 YEAR
Job Description & How to Apply Below
Position: Forward Deployed Engineer (Python, AI/ML, Generative AI)
Location: Greater London

  • We are looking for a Forward Deployed AI Engineer to work closely with clients to identify, prototype, and deploy AI-powered solutions to real-world business challenges
  • This is a highly hands-on, customer-facing role combining AI engineering, software development, solution architecture, and consulting. You will work directly with users and stakeholders to understand their needs, rapidly build solutions, and iterate based on real-world feedback
  • Work directly with clients to understand business challenges, workflows, data, systems, and technical requirements
  • Translate ambiguous problems into practical AI and software solutions
  • Design, build, and deploy AI-powered applications, agents, copilots, and intelligent workflows
  • Integrate LLMs, Generative AI, APIs, enterprise systems, and data sources
  • Rapidly prototype solutions and validate them with users
  • Develop supporting APIs, services, data pipelines, and application infrastructure
  • Design scalable, secure, and maintainable technical architectures
  • Implement evaluation, monitoring, observability, and feedback mechanisms for AI solutions
  • Collaborate with product, data, engineering, and business teams to move successful prototypes into production
  • Communicate technical concepts and recommendations clearly to both technical and non-technical stakeholders
  • What Success Looks Like:
  • You will be successful when you can take an ambiguous customer problem and turn it into a working AI capability that people actually use
  • The role requires someone who can move quickly between:
  • Customer problem → solution design → architecture → code → prototype → user feedback → iteration → production

The ideal candidate is a strong engineer who is comfortable moving between customer conversations, architecture, coding, prototyping, and production delivery

Ideal Candidate
  • LLMs / Generative AI — Hands-on experience building applications using LLMs and Generative AI
  • Type Script — Experience developing modern applications or services
  • Customer-Facing / Consulting — Ability to work directly with clients and translate business problems into technical solutions
  • Solution Architecture — Ability to design end-to-end solutions that are scalable, secure, and aligned to business objectives
  • AI/ML Integration — Experience integrating AI/ML capabilities into applications and workflows
  • Cloud Platforms — Experience with AWS, Azure, and/or GCPPython
  • Python — Strong software engineering and application development experience
  • APIs & System Integration — Experience with APIs, enterprise systems, third-party platforms, and data sources
  • Agent Orchestration — Experience or understanding of AI agents, tool calling, agentic workflows, or orchestration frameworks
  • Application Engineering — Experience building, testing, and deploying production applications
  • Experience building and deploying AI/ML or Generative AI applications
  • Strong communication and stakeholder management skills
  • Ability to work independently within complex enterprise environments
  • Ability to rapidly prototype and turn ideas into working software
  • Strong problem-solving skills and comfort working with incomplete or evolving requirements
  • Typically 5+ years’ experience in software engineering, AI/ML engineering, or a related technical discipline
  • A product-oriented mindset focused on solving the user’s problem rather than simply delivering requirements
  • Experience with RAG, vector databases, embeddings, and semantic search
  • Consulting, systems integration, or professional services experience
  • Experience with AI agent frameworks and orchestration platforms
  • Experience with Docker, Kubernetes, CI/CD, or Infrastructure as Code
  • Experience taking AI/ML prototypes through to production
  • Experience working with large or complex enterprise customers
  • Experience working in regulated or highly controlled environments
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