Infoplus Technologies UK Limited
Artificial Intelligence Engineer

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Job Description: GenAI Python Engineer
Role Summary
Seeking a GenAI Engineer with strong hands-on experience in building end-to-end AI applications. The role requires integrating data from multiple systems, extracting and parsing information from documents and images, interacting with structured databases, storing parsed content in a vector database, and implementing robust retrieval pipelines. The engineer must also ensure solution quality through evaluation frameworks, ground-truth validation, and defined performance metrics.
Key Responsibilities
- Design and build GenAI/RAG-based applications using data from multiple enterprise systems.
- Integrate with structured and unstructured data sources, including databases, APIs, files, and document repositories.
- Develop pipelines to parse and extract data from documents and images using OCR, document intelligence, and related tools.
- Process and structure extracted content for downstream AI use cases.
- Store parsed and chunked content in a vector database and manage embeddings effectively.
- Implement and optimize retrieval pipelines, including chunking, indexing, metadata tagging, filtering, and reranking.
- Build workflows to interact with relational and enterprise databases for querying and enrichment.
- Ensure the application follows strong evaluation practices, including accuracy, groundedness, relevance, hallucination checks, and response quality against ground truth.
- Work closely with architects, platform teams, and business stakeholders to deliver scalable and secure solutions.
- Follow enterprise standards for security, governance, observability, and performance.
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.
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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.
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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.
Required Skills and Experience
- Strong experience in AI/ML engineering, with hands-on exposure to Generative AI use cases.
- Experience in building RAG applications in enterprise environments.
- Strong knowledge of document parsing, OCR, and image-based data extraction.
- Experience with LLM orchestration frameworks and prompt design.
- Experience with vector databases and semantic search.
- Very Strong programming skills in Python.
- Experience working with SQL/NoSQL databases and enterprise data integration patterns.
- Understanding of evaluation frameworks for GenAI systems using benchmark datasets and ground-truth-based validation.
- Experience in building scalable APIs/services and production-grade AI workflows.


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Preferred Skills
- Experience with Azure-based AI stack.
- Experience with high-volume document processing.
- Familiarity with enterprise architecture, security, and compliance controls.
- Exposure to monitoring, model evaluation, and AI observability tools.
Preferred Profile
- Able to independently build and deploy GenAI applications from ingestion to retrieval and evaluation.
- Strong problem-solving skills with a practical implementation mindset.
- Comfortable working across data engineering, AI engineering, and application integration.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
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