At a Glance
- Tasks: Lead the design of innovative AI solutions using LangGraph and enterprise architectures.
- Company: Join a forward-thinking tech company focused on AI and cloud solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on mentorship and career advancement.
- Why this job: Shape the future of AI technology and make a significant impact in the industry.
- Qualifications: Experience in solution architecture and hands-on with LangGraph-based applications.
The predicted salary is between 76662 - 93698 £ per year.
Requirements
We are looking for an experienced
Solution Architect with hands-on experience designing and deploying Lang Graph-based AI solutions to lead the architecture of enterprise agentic AI platforms and applications.
You will work with business and technology stakeholders to identify high-value AI opportunities and translate them into secure, scalable, and production-ready architectures.
The role combines
AI architecture, enterprise integration, cloud engineering, agentic AI, security, governance, and stakeholder leadership .
You will be expected to understand Lang Graph at a practical level and be able to challenge architectural decisions, guide engineering teams, and ensure that AI solutions can operate reliably at enterprise scale.
Requirements
- AI Solution Architecture
- Lead the architecture and design of enterprise AI agent and agentic workflow solutions
- Design Lang Graph-based architectures for single-agent and multi-agent applications
- Translate business requirements, processes, SLAs, security requirements, and technical constraints into solution architectures
- Evaluate architectural alternatives and document key technical decisions and trade-offs
- Define reusable architecture patterns for agentic AI solutions
- Enterprise Agent Architecture
• Design architectures incorporating
- LLMs
- Lang Graph
- RAG
- Enterprise data
- APIs and business systems
- Workflow engines
- Human approval processes
- Observability
- Security and governance
- Define appropriate boundaries between AI reasoning and deterministic business logic
- Design state management, persistence, recovery, and long-running agent workflows
- Determine when to use single-agent, multi-agent, or conventional application architectures
- Cloud and Platform Architecture
- Design scalable AI application architectures on AWS, Azure, or GCP
- Define compute, networking, storage, API, security, and platform requirements
- Design architectures suitable for enterprise-scale production workloads
- Evaluate cloud services and AI platform capabilities based on performance, security, scalability, and cost
- Work with platform engineering and Dev Ops teams to establish deployment standards
- Integration Architecture
- Design integration between AI agents and enterprise applications, APIs, databases, and Saa S platforms
- Define secure mechanisms for agent tool access and business-system interactions
- Design authentication, authorisation, secrets management, and access-control approaches
- Ensure AI-driven actions are traceable, auditable, and appropriately governed
- AI Security and Governance
- Establish security and governance principles for enterprise AI agents
• Address risks including
- Prompt injection
- Data leakage
- Unauthorised tool usage
- Excessive agent permissions
- Inaccurate or unsafe actions
- Sensitive-data exposure
- Define appropriate human-in-the-loop controls
- Ensure solutions comply with organisational security, privacy, regulatory, and responsible-AI requirements
- AI Evaluation and Observability
- Define architecture for AI application monitoring and observability
- Establish approaches for evaluating agent accuracy, reliability, latency, cost, and task completion
- Define appropriate logging, tracing, metrics, and alerting
- Establish operational processes for monitoring and continuously improving production agents
- Stakeholder and Technical Leadership
- Work directly with senior business and technology stakeholders to define AI strategies and roadmaps
- Lead architecture workshops and technical design sessions
- Communicate complex AI concepts and architectural trade-offs to technical and non-technical audiences
- Provide technical direction to AI engineers, developers, data teams, and platform engineers
- Review solution designs and ensure alignment with enterprise architecture standards
- Mentor engineering teams and promote reusable AI architecture patterns
- Required Experience
- Significant experience in solution architecture, software architecture, AI architecture, or a related role
- Hands-on experience designing and deploying Lang Graph-based AI applications or agentic workflows
- Strong understanding of LLM application architectures
- Experience with enterprise AI/ML solutions in production
- Strong understanding of RAG, tool calling, agent orchestration, and human-in-the-loop patterns
- Strong experience with at least one major cloud platform: AWS, Azure, or GCP
- Strong understanding of enterprise integration patterns and APIs
- Experience with security, governance, observability, and operational requirements for production systems
- Strong technical understanding of Python and modern software engineering practices
Desirable Experience
- Lang Chain / Lang Smith
- Multi-agent architectures
- Enterprise RAG platforms
- Vector databases
- Kubernetes
- Event-driven architectures
- Microservices
- Infrastructure as Code
- CI/CD
- MLOps / LLMOps
- AI security
- Responsible AI
- Large-scale enterprise transformation
- Experience working directly with senior client stakeholders
- #J-18808-Ljbffr
Solution Architect - LangGraph & Agentic AI employer: Belmont Lavan
Our Client stands out as an exceptional employer in the Prop-Tech and Data sector, offering a dynamic work environment that fosters innovation and collaboration. With a flat organisational structure and a strong emphasis on employee growth, they provide ample opportunities for professional development, mentorship, and flexible working arrangements. Located in the UK, employees enjoy a supportive culture that prioritises well-being, including generous holiday allowances and lifestyle benefits, making it an ideal place for passionate developers to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Solution Architect - LangGraph & Agentic AI
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Belmont Lavan or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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✨Tap into Online Developer Communities
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We think you need these skills to ace Solution Architect - LangGraph & Agentic AI
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Belmont Lavan.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Belmont Lavan and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Belmont Lavan
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Belmont Lavan uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
