At a Glance
- Tasks: Design and operationalise LLM-driven comparison workflows for decision-ready reports.
- Company: Join a forward-thinking tech company with a focus on AI innovation.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with a commitment to inclusive recruitment and career advancement.
- Why this job: Make an impact in AI by blending cutting-edge tech with real-world applications.
- Qualifications: Strong skills in prompt engineering, context engineering, and Python are preferred.
The predicted salary is between 60000 - 80000 £ per year.
We are hiring an AI Engineer to design and operationalize LLM-driven comparison workflows that produce decision-ready comparison reports across Salesforce orgs and codebases. The role focuses on prompt engineering, context engineering, and agentic orchestration to generate structured outputs (including AST or AST-like representations for code). You will blend deterministic Graph DB reports with non-deterministic LLM insights, and enable human-in-the-loop validation.
Hybrid Working
The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
Your Role
- Design, iterate, and maintain prompt + context strategies to generate consistent, structured comparison outputs (JSON schemas, diff formats, summaries).
- Build and run agent workflows to orchestrate multi-step comparison tasks (planning, tool calls, retries, fallbacks, state management).
- Produce code-aware comparisons using AST or similar structural representations (e.g., class/method-level diffs, dependency summaries, refactor suggestions).
- Integrate deterministic Graph DB findings (commonality/variation, dependency paths, lineage) into LLM context to improve reliability and traceability.
- Implement output guardrails: schema validation, format constraints, confidence scoring, and consistency checks across runs.
- Support MCP-based integrations where required to connect tools, enforce controlled context, and standardize tool interfaces for agents.
- Partner with Salesforce engineers/architects to validate findings, refine templates, and ensure outputs are reviewable and audit-friendly.
Your Skills
- Strong prompt engineering and context engineering (structured prompting, tool/function calling, grounding strategies, hallucination mitigation).
- Hands-on experience building LLM agents and orchestration (multi-step workflows, state/memory, tool routing, error handling).
- Ability to generate structured code analysis outputs (AST/parse-tree approaches, semantic diffs, dependency extraction, refactoring insights).
- Experience combining deterministic outputs (Graph DB queries, rule checks) with non-deterministic LLM reasoning in a controlled pipeline.
- Python is a strong plus (automation scripts, parsers, report generators, lightweight services).
- Salesforce metadata understanding is a plus (objects/fields, flows, profiles/permsets, dependency concepts, cross-org comparison needs).
- Proven experience with Claude for structured outputs and agentic workflows (prompt patterns, tool-use/function calling, long-context strategies).
- Familiarity with Claude-friendly prompt hygiene: explicit schemas, deterministic formatting, step constraints, and robust self-check prompts.
- Experience using Claude in MCP-based tool ecosystems (defining tools, controlling context sources, safe orchestration patterns).
EEO Statement
We are a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who declare they have a disability and meet the minimum essential criteria for the role. Please opt in during the application process.
AI Engineer - Prompt & Context Engineering (Graph + LLM Comparison) employer: Moonfire
Join a forward-thinking company that values innovation and collaboration, where as an AI Engineer, you will have the opportunity to work on cutting-edge LLM-driven projects in a hybrid working environment. Our inclusive culture fosters professional growth, offering continuous learning opportunities and the chance to partner with top Salesforce engineers, ensuring your contributions are impactful and recognised. With a commitment to diversity and a supportive atmosphere, we provide a rewarding workplace for those looking to make a difference in the tech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer - Prompt & Context Engineering (Graph + LLM Comparison)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with LLMs or Salesforce. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your prompt engineering and context strategies. Share examples of your work with structured outputs and agent workflows to impress potential employers.
✨Tip Number 3
Prepare for interviews by practising common questions related to AI engineering and LLMs. Be ready to discuss your experience with Python and how you've tackled challenges in previous projects.
✨Tip Number 4
Don't forget to 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 are proactive about their job search!
We think you need these skills to ace AI Engineer - Prompt & Context Engineering (Graph + LLM Comparison)
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with prompt engineering and context strategies. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Show Off Your Technical Skills:Don’t forget to mention your hands-on experience with Python and any familiarity with Salesforce metadata. We’re keen on seeing how you’ve used these tools in past roles, so give us some juicy examples!
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, especially when it comes to complex topics like LLM-driven workflows and structured outputs. Make it easy for us to see your expertise!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Moonfire
✨Master the Art of Prompt Engineering
Get familiar with structured prompting techniques and grounding strategies. Prepare examples of how you've successfully mitigated hallucinations in previous projects, as this will showcase your hands-on experience in prompt engineering.
✨Showcase Your Workflow Orchestration Skills
Be ready to discuss your experience with building multi-step workflows and state management. Bring specific examples of how you've handled error management and tool routing in past roles to demonstrate your capability in orchestrating complex tasks.
✨Demonstrate Your Code Analysis Expertise
Prepare to explain your approach to generating structured code analysis outputs, like AST or semantic diffs. Highlight any projects where you combined deterministic outputs with LLM reasoning, as this aligns perfectly with the role's requirements.
✨Familiarise Yourself with Salesforce Metadata
If you have experience with Salesforce, brush up on your knowledge of objects, fields, and cross-org comparison needs. Being able to discuss how you've worked with Salesforce metadata will give you an edge in the interview.
