At a Glance
- Tasks: Deploy innovative tech solutions at client sites and solve real-world problems.
- Company: Join a cutting-edge company transforming enterprise data into actionable insights.
- Benefits: Competitive salary, health benefits, remote work options, and growth opportunities.
- Other info: Dynamic role with opportunities to work on complex data environments.
- Why this job: Make a tangible impact by automating workflows in pharma and finance sectors.
- Qualifications: Experience in pharma or finance, strong graph literacy, and excellent client communication skills.
The predicted salary is between 60000 - 80000 £ per year.
About us: We build the governed context layer for the agentic enterprise. We take complex, heterogeneous enterprise data and auto-generate knowledge graphs from it — no manual schema design, no ontology engineering. Those graphs power LLM agents that automate workflows that previously required skilled human judgement and hours of manual work.
The role: We sell outcomes, not technology. The core engineering team builds the product. You deploy it. You work at client sites on real problems: validating auto-generated graphs, identifying what workflows are worth automating, building the agent prototype that makes it tangible, and enabling implementation partners to take it into production. It's a technical role with a client-facing orientation. Equally comfortable reading a graph query and presenting to a CTO. Not a demo engineer — someone who can configure the product, break it, fix it, and explain why it matters to someone who doesn't know what a triple is.
Verticals:
- Pharma & Health: Competitive intelligence synthesis, KOL engagement routing, MLR risk flagging, regulatory change impact assessment. Clinical data, market signals, HCP networks, and regulatory history connected in one graph.
- Finance: Product-to-client matching against versioned eligibility rules, multi-hop contract reasoning, governed advisory with full audit trail. Products, rules, and decisions connected across silos.
What you'll own:
- Getting the graph live. Figure out which connectors a client needs, work with the core team to configure them, inspect the auto-generated graph for correctness — entity coverage, relationship accuracy, gaps that'd break a downstream agent.
- Mapping what's worth automating. Find the workflows that are slow or error-prone because the right context isn't accessible at decision time. Graph analytics surfaces the structure; the goal is always the workflow it unlocks.
- Building the proof of value. A working prototype on real data — credible enough to get a yes, specific enough to hand off. Integrated with the client's existing LLM. Runs live. Tells a clear story.
- Enabling partners. Make the technical handoff to implementation partners work. They build the production system. You make sure they have everything they need to do it without us in the room.
What you'll bring:
- Domain knowledge. Real experience in pharma, finance, or both. Knows what's worth automating and why.
- Graph literacy. Can query and inspect graph structure. Knows whether a generated graph is fit for a workflow.
- Agent fluency. Has built agents that do something real. Knows what goes wrong and why.
- Integration thinking. Can map a client's data environment to the connectors needed to bring it into the graph.
- Demo craft. Builds things that work live. Reliable, clear, polished enough for a sales process.
- Client communication. Holds a room of senior stakeholders. Moves between technical and commercial without losing either audience.
Nice to have:
- Workflow automation in pharma or finance
- GraphRAG and multi-hop reasoning
- Graph quality assessment
- SI / implementation partner experience
- Regulatory data fluency (MiFID II, MLR, ACPR)
- Prior FDE or technical consulting background
- Streamlit or equivalent rapid prototyping
Why this role: Most enterprise AI deployments stall between the model and the workflow. The data's messy, the context is missing, and no one's figured out how to make the agent reliably do the thing the business actually needs. That's exactly the problem this role exists to solve — and you'll be solving it across some of the most complex data environments in pharma and finance, with a product that's built specifically for it. Architectural input, real client problems, and outcomes you can point to.
Forward Deployed Engineer in Slough employer: ENAIBLE TALENT
As a Forward Deployed Engineer, you will thrive in a dynamic work culture that prioritises innovation and collaboration, working directly with clients to tackle real-world challenges in the pharma and finance sectors. Our commitment to employee growth is evident through hands-on experience with cutting-edge technology and the opportunity to engage with senior stakeholders, ensuring that your contributions lead to meaningful outcomes. Join us in a role where your technical expertise meets client-facing engagement, all within an environment that values creativity and problem-solving.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed Engineer in Slough
✨Tip Number 1
Get to know the company inside out! Research their products, values, and recent projects. This way, when you chat with them, you can show off your knowledge and passion for what they do.
✨Tip Number 2
Practice your technical skills and be ready to demonstrate them. Whether it's querying graphs or discussing workflows, being hands-on will help you stand out. We want to see you in action!
✨Tip Number 3
Don’t shy away from asking questions during interviews. It shows you're engaged and helps you understand how you can contribute. Plus, it gives you a chance to showcase your client communication skills!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Forward Deployed Engineer in Slough
Some tips for your application 🫡
Show Your Technical Skills:Make sure to highlight your technical expertise in your application. We want to see how you can read graph queries and understand complex data structures, so don’t hold back on showcasing your graph literacy!
Tailor Your Experience:When writing your application, connect your past experiences to the role. If you've worked in pharma or finance, share specific examples of how you've tackled similar challenges. We love seeing how your background aligns with what we do!
Communicate Clearly:Since this role involves client-facing interactions, your written application should reflect your ability to communicate complex ideas simply. Use clear language and avoid jargon where possible — we want to see how you can bridge the gap between technical and commercial audiences.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at ENAIBLE TALENT
✨Know Your Graphs
Make sure you brush up on your graph literacy before the interview. Be ready to discuss how you would inspect and validate auto-generated graphs, and be prepared to explain what makes a graph fit for a workflow. This will show that you understand the technical side of the role.
✨Understand the Client's Needs
Research the company and its clients in the pharma and finance sectors. Think about specific workflows that could benefit from automation and be ready to share your insights. This demonstrates your domain knowledge and shows that you can think critically about real-world applications.
✨Showcase Your Prototyping Skills
Prepare to discuss any previous projects where you've built working prototypes or agents. Highlight how you integrated them with existing systems and the impact they had. This will illustrate your hands-on experience and ability to deliver tangible results.
✨Communicate Effectively
Practice explaining complex technical concepts in simple terms. You might need to present to senior stakeholders who may not have a technical background. Being able to switch between technical jargon and layman's terms will be key to showing your client communication skills.
