YADAQ
Senior Founding Platform Engineer (Backend & AI)
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
YADAQ | Remote | Founding Technical Team
Company Description
YADAQ is a pre-seed research technology company developing intelligent tools for how people capture, organise and use knowledge.
Operating at the intersection of AI, research technology, EdTech and LegalTech, YADAQ addresses a persistent problem in research-intensive work: valuable information is often encountered across fragmented sources and workflows, making it unnecessarily difficult and time-consuming to find and use again when it matters.
Built around the principle “research that remembers,” YADAQ is focused on making knowledge-intensive research more intuitive, efficient and accessible, with applications across academic and professional knowledge work.
The Role
We are seeking an experienced Senior Founding Platform Engineer (AI) to take substantial technical ownership of YADAQ's core platform development.
This is a hands-on, senior engineering position requiring demonstrated expertise in backend architecture, applied AI systems, retrieval infrastructure and production-grade software development.
Working directly with product leadership and the founding technical team, you will help define the technical architecture, make critical engineering decisions and lead implementation of the systems underpinning our research platform.
We are looking for an engineer who can independently design and deliver complex systems, not someone seeking their first opportunity to work with AI.
The role combines senior-level engineering execution with the ownership, adaptability and judgement required in a zero-to-one venture.
Key Responsibilities
Platform Architecture & Backend Engineering
- Architect, develop and maintain scalable backend services, APIs, databases and core platform infrastructure.
- Make informed architectural decisions concerning system design, performance, security, maintainability and scalability.
- Design robust data models, authentication systems and access-control mechanisms.
- Establish appropriate engineering standards for testing, deployment, documentation and observability.
- Identify and resolve architectural bottlenecks, performance issues and infrastructure risks.
Applied AI & Retrieval Systems
- Design and implement production-oriented retrieval-augmented generation (RAG) pipelines.
- Develop semantic search capabilities using embeddings, vector databases and hybrid retrieval approaches.
- Build document ingestion, parsing, chunking, indexing and retrieval pipelines.
- Integrate and orchestrate LLM APIs within reliable backend services.
- Implement source-grounded retrieval, metadata management and traceability mechanisms.
- Evaluate retrieval relevance, grounding, latency, reliability and inference costs.
- Apply techniques such as reranking, retrieval optimisation and structured evaluation to improve system performance.
- Make practical decisions about model selection, infrastructure and cost-performance trade-offs.
Reasons to use Rodeo
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.
It 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.
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.
Technical Ownership & Execution
- Translate product requirements into scalable technical solutions and executable engineering priorities.
- Take responsibility for delivering substantial components of the MVP from architecture through deployment.
- Collaborate with other founding engineers and technical leadership on system integration and development priorities.
- Review technical approaches, challenge assumptions constructively and identify pragmatic implementation strategies.
- Contribute to longer-term architectural planning as the platform moves towards institutional deployment.
Essential Qualifications - Mandatory
Applicants must demonstrate substantial professional experience in backend/platform engineering and hands-on applied AI development.
Senior Engineering Experience
- Typically 5+ years of professional software engineering experience, including significant backend or platform engineering responsibility.
- Proven experience designing, building and deploying production-grade applications.
- Advanced proficiency in Python, with experience using frameworks such as FastAPI or Django.
- Strong understanding of API architecture, asynchronous processing, distributed systems and database design.
- Production experience with PostgreSQL or comparable relational databases.
- Practical experience with cloud infrastructure (AWS, GCP or Azure), Docker, CI/CD and deployment workflows.
- Demonstrated ability to make independent architectural decisions and take ownership of complex engineering deliverables.
Applied AI Engineering - Essential
- Demonstrable professional experience developing and deploying LLM-powered applications or AI-enabled backend systems.
- Hands-on experience designing and implementing RAG architectures.
- Strong working knowledge of semantic search, embeddings, vector similarity search and retrieval pipelines.
- Experience with vector databases or search infrastructure such as pgvector, Qdrant, Pinecone, Weaviate or Elasticsearch.
- Experience integrating LLM APIs, managing model interactions and optimising inference costs.
- Understanding of retrieval evaluation, hallucination mitigation, source grounding and AI system reliability.
- Ability to explain the technical trade-offs behind previously implemented AI architectures.
Senior-Level Ownership
- Evidence of independently delivering substantial backend or AI infrastructure components.
- Ability to move from technical requirements to architecture, implementation, testing and deployment.
- Strong debugging, systems-thinking and technical problem-solving capabilities.
- Experience collaborating across engineering and product functions.
- Clear technical communication and the confidence to challenge architectural decisions constructively.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Highly Desirable
- Experience with hybrid search, reranking, retrieval evaluation frameworks and advanced RAG architectures.
- Experience with document intelligence, PDF parsing, OCR, unstructured data processing or knowledge-management systems.
- Familiarity with LangChain, LlamaIndex or equivalent orchestration frameworks, including the ability to build without them.
- Experience designing multi-tenant SaaS applications, permission models or enterprise-grade infrastructure.
- Knowledge of data provenance, citation grounding and information retrieval evaluation.
- Previous senior engineering experience at a US or European technology company.
- Experience as a founding engineer, technical lead or early engineering hire in a venture-backed startup.
Location & Working Arrangement
Remote - international applications welcome.
Preference will be given to:
- Engineers based in the United Kingdom; and/or
- International engineers with demonstrable experience working for US or European technology companies, preferably in senior engineering roles.
Candidates must have strong professional English communication skills and sufficient working-hour overlap with the UK team.
Compensation & Commitment
YADAQ is a pre-seed venture expanding its founding technical team.
This is an equity-based founding opportunity with no guaranteed salary at the current stage.
Equity participation will be negotiated according to seniority, technical responsibilities, commitment and anticipated long-term contribution, subject to formal agreement and vesting.
The position requires sustained, meaningful involvement and substantial hands-on engineering contribution.
Any engagement will be structured in accordance with applicable employment and compensation requirements.
Candidate Profile
We are looking for an experienced engineer who has already built and deployed sophisticated technical systems and is now interested in applying that expertise to an early-stage venture.
You should combine deep technical competence with sound engineering judgement, commercial awareness and the ability to execute without extensive supervision.
This is not an entry-level AI role. Candidates whose experience is limited to academic projects, introductory AI courses, prompt engineering or no-code AI tools will not meet the technical requirements.
Application Requirements
Please submit your CV together with brief details of:
- A production AI or RAG system you personally designed or implemented, including your specific technical contribution.
- Your experience with backend architecture, vector databases and cloud deployment.
- Your availability, location and experience working with US or European engineering teams.
GitHub repositories, technical portfolios or links to deployed applications are strongly encouraged.
“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.”
Jessica, London