At a Glance
- Tasks: Lead AI solution delivery and build innovative workflows in a hybrid work environment.
- Company: Dynamic tech firm focused on AI and automation solutions.
- Benefits: Competitive pay, flexible working, and opportunities for professional growth.
- Other info: Collaborative culture with exciting projects in Corporate and Compliance sectors.
- Why this job: Join a cutting-edge team and make a real impact with AI technology.
- Qualifications: Experience in Azure, AI development, and strong problem-solving skills.
The predicted salary is between 60000 - 80000 £ per year.
Role type: Contract (Inside IR35)
Location: London
Work mode: Hybrid – at least 1 or 2 days a week onsite
Key Responsibilities
- Delivery & Execution
- Lead end-to-end solution delivery across Corporate, Compliance, Legal, and Risk Management domains — from design and build through UAT and production deployment.
- Own release readiness: manage UAT-to-production transitions, validate operational quality, and ensure solutions meet the firm's engineering and compliance standards.
- Build and maintain CI/CD pipelines and DevOps processes on Azure-based platform, working within established GitOps and Flux deployment patterns.
- Manage delivery across multiple concurrent workstreams, coordinating with engineering, product, and business teams to maintain momentum and remove blockers.
- AI-Enabled Solution Design & Build
- Apply AI tools, agent frameworks, and workflow orchestration to solve business-critical problems — selecting the right approach and model for each use case rather than defaulting to the most complex solution.
- Design and implement agent workflows on Axon SDK and Azure AI Foundry, integrating Azure OpenAI, Document Intelligence, and AI Search.
- Build multi-step automations and AI pipelines using Temporal as the firm's enterprise workflow orchestrator.
- Integrate solutions with data platform — consuming Snowflake data through the Delphi data PaaS, connecting to operational systems, and working within the firm's data governance model.
- Expose and consume capabilities through internal Model Context Protocol (MCP) broker pattern.
- Stakeholder Engagement
- Work directly with business leads, product managers, and domain teams to gather requirements, shape use cases, and translate them into clear, deliverable technical solutions.
- Communicate progress, risks, and trade-offs clearly to both technical leads and senior business stakeholders.
- Contribute to solution documentation, runbooks, and knowledge transfer as a standard part of delivery.
Required Skills & Experience
- Engineering & Delivery
- Proven track record of end-to-end solution delivery in production enterprise environments — design through deployment and ongoing operation.
- Strong hands-on experience with Azure: AKS, Azure AI services, CI/CD pipeline implementation, and DevOps practices.
- Solid understanding of GitOps deployment patterns and Flux-based release workflows.
- Experience writing infrastructure configuration — Terraform or equivalent IaC — in a team-managed environment.
- Comfortable working across the full delivery lifecycle including UAT coordination, operational readiness, and post-launch support.
- AI & Automation
- Deep practical experience with AI development workflows: agent design, prompt engineering, workflow orchestration, and model selection.
- Hands-on experience with AI frameworks and orchestration tools — applied to real delivery problems, not proof-of-concept work.
- Fluency with AI-assisted development tooling (Cursor, Claude, Codex) as a primary accelerant for engineering delivery.
- Working knowledge of Azure AI Foundry, Azure OpenAI, Document Intelligence, and AI Search is strongly preferred.
- Experience with Temporal or a comparable workflow orchestration platform is a plus.
- Domain & Environment
- Exposure to Corporate, Compliance, Legal, or Risk Management functions; understanding of the domain accelerates delivery significantly.
- Strong communication and stakeholder management skills; ability to operate credibly at both working and senior levels.
- Ownership mindset, high accountability, and the flexibility to meet delivery commitments in a demanding environment.
AI & Agents
- Axon SDK · Azure AI Foundry · Azure OpenAI · Document Intelligence · AI Search · MCP broker
Orchestration
- Temporal — agent runs, ETL pipelines, multi-step automations
Data
- Snowflake via Delphi · Event Hubs · ADLS Gen2 · Cosmos DB · Redis · EDB Postgres
Cloud & Deployment
- Azure · AKS · Flux GitOps · GitHub Actions · Terraform central module catalog
Observability
- Datadog · Prometheus / Grafana · PagerDuty
ITSM & Identity
- ServiceNow · Jira · Okta (OIDC) · Active Directory
Forward Deployed AI Engineer in London employer: ixceed solutions
As a Forward Deployed AI Engineer at our London office, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. We offer a hybrid work model, competitive benefits, and ample opportunities for professional growth, ensuring that you can make a meaningful impact while advancing your career in cutting-edge AI solutions. Join us to be part of a forward-thinking team that values your contributions and supports your development in a vibrant city.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed AI Engineer in London
✨Showcase Your Skills with a Public Portfolio
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✨Leverage Local Networking Opportunities
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We think you need these skills to ace Forward Deployed AI Engineer in London
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Forward Deployed AI Engineer at ixceed solutions, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
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Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at ixceed solutions.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at ixceed solutions
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
✨Be Ready to Dive Deep into Technical Questions
Expect to encounter some technical grilling during the interview. Prepare to discuss statistical methods, algorithms, or maybe even tackle a live coding challenge. We should brush up on tools like Python, R, or SQL—those are key players in the data science field. Don't just know them; be ready to explain your thought process!
✨Help Them Understand Your Work Style
Freelance gigs often mean you'll be working independently, so we need to convey our self-motivation and time management skills. Be prepared to talk about how you’ve handled multiple projects or met tight deadlines before. Sharing your approach to client communication can also give them confidence in your ability to deliver remotely.
✨Pitch Your Value Proposition
When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
