Vallum Associates
Agentic AI Engineer

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Description
We're looking for an Agentic AI Engineer to join our team. In this role, you will design and implement agentic AI workflows that automate and accelerate software development activities, including coding, testing, quality assurance, and continuous integration. You will translate business requirements into practical AI-driven engineering solutions integrated with repositories, architecture, and CI/CD pipelines. The position involves building safe, controllable, and reusable AI patterns, ensuring proper validation, quality gates, and human oversight.
Responsibilities
- Translate business requirements into agentic AI workflows across coding, review, testing, and defect resolution
- Build connected AI-driven pipelines that can develop code, execute tests, analyze failures, and refine implementations iteratively
- Assess existing repository, architecture, and technology stack before proposing automation solutions
- Embed validation controls, quality gates, evidence capture, safe stopping conditions, and human approval checkpoints in solutions
- Package and integrate agentic AI workflows for reuse across teams and development environments
- Ensure measurable outcomes aligned with quality, security, and regulatory compliance
- Collaborate with engineering, QA, and DevOps teams to scale AI-driven capabilities across the organization
- Support continuous improvement and responsible AI practices
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements (Must Have Skills)
- Strong hands-on background in software engineering, SDET, quality engineering, data engineering, DevOps, or platform engineering
- Proven experience using agentic AI tools such as GitHub Copilot and/or Databricks Genie
- Expertise in multi-step AI workflows for development lifecycle: code generation, review, testing, and iterative refinement
- Proficiency in automated testing, shift-left quality practices, Git-based workflows, pull requests, and CI/CD
- Ability to translate business problems into technical AI solutions with measurable control points
- Experience embedding human-in-the-loop validation, safe failure handling, and reusable automation patterns


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Nice to Have Skills
- Experience creating custom Copilot agents or repository-aware AI prompts
- Familiarity with Databricks workflows, notebooks, pipelines, and data-quality engineering
- Knowledge of AI agent evaluation, regression testing, and performance benchmarking
- Exposure to static analysis, security testing, observability solutions, and responsible AI governance
- Experience scaling AI engineering capabilities across large programs or multiple teams
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