AI Engineer - Prompt & Context Engineering (Graph + LLM Comparison)
Capgemini · London, England, United Kingdom
- On site
- Full-time
- $120,000 / year
- London, England, United Kingdom
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Job highlights
- Design LLM workflows for comparison reports.
- Orchestrate multi-step agent tasks.
- Analyze code using AST representations.
- Combine Graph DB insights with LLM.
- Implement output validation and guardrails.
About the role
About the AI Engineer Role
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. Salesforce metadata familiarity is a plus; Python is beneficial for automation and tooling.
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).
Disability Confident Employer
Capgemini is proud to be 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.
Make It Real (What it means for you)
- You’d be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.
- You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.
- You will be joining one of the World’s Most Ethical Companies®, as recognised by Ethisphere® for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.
Why You Should Consider Capgemini
Growing clients’ businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you’ll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what’s possible. It’s why, together, we seek out opportunities that will transform the world’s leading businesses, and it’s how you’ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you’ll build the skills you want. You’ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.
About Capgemini
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Key Skills/Competency
- AI Engineer
- Prompt Engineering
- Context Engineering
- LLM
- Agentic Orchestration
- Graph DB
- Python
- Salesforce
- Code Analysis
- Structured Outputs
Skills & topics
- AI Engineer
- Prompt Engineering
- Context Engineering
- LLM
- Agentic Orchestration
- Graph DB
- Python
- Salesforce
- Code Analysis
- Structured Outputs
- Artificial Intelligence
- Machine Learning
- Software Engineering
- Cloud Computing
- Data Science
- Developer
- Engineer
- Hybrid
- Consulting
- Technology
How to get hired
- Tailor your resume: Highlight AI, LLM, prompt engineering, and Python skills.
- Showcase relevant experience: Detail projects involving agentic workflows and structured outputs.
- Address prompt engineering: Emphasize structured prompting, function calling, and hallucination mitigation.
- Demonstrate Python proficiency: Provide examples of automation scripts or parsers.
- Research Capgemini's values: Align your application with their focus on innovation and ethics.
Technical preparation
Behavioral questions
Frequently asked questions
- What specific LLM experience is most valuable for the AI Engineer role at Capgemini?
- Hands-on experience building LLM agents and orchestration, particularly with frameworks like Claude for structured outputs and agentic workflows, is highly valued. This includes proficiency in prompt patterns, tool-use, function calling, and long-context strategies.
- How important is Python for this AI Engineer position at Capgemini?
- While not strictly required, Python is a strong plus. Proficiency in Python is beneficial for automation scripts, parsers, report generators, and developing lightweight services to support the AI Engineer's tasks.
- What does 'agentic orchestration' mean in the context of this AI Engineer job?
- Agentic orchestration involves building and running workflows for multi-step AI tasks. This includes planning, tool calls, error handling, retries, fallbacks, and managing the state of the AI agent throughout its execution.
- How does Capgemini support employee wellbeing for its AI Engineers?
- Capgemini emphasizes employee wellbeing, as evidenced by their 'Great Place to Work for Wellbeing' accreditation. They offer trained Mental Health Champions and invest in wellbeing apps like Thrive and Peppy.
- Is Salesforce metadata knowledge necessary for the AI Engineer role?
- Familiarity with Salesforce metadata is considered a plus for this AI Engineer role. Understanding objects, fields, flows, profiles, and dependency concepts can enhance your ability to perform cross-org comparisons.
- What are the opportunities for training and development at Capgemini for an AI Engineer?
- Capgemini promotes a 'learning for life' mindset with numerous training and development opportunities. This includes access to think tanks, hackathons, over 250,000 courses, and external certifications from providers like AWS and Microsoft.
- How does Capgemini approach inclusive recruitment for its AI Engineer roles?
- Capgemini is a Disability Confident Employer. They offer an interview to candidates who declare a disability and meet the minimum essential criteria for the role, with an option to opt-in during the application process.
- What is the expected work arrangement for the AI Engineer role at Capgemini?
- This role operates on a hybrid working model. Employees will blend working from company offices, client sites, and home, with the understanding that 100% remote work is not an option.