Full Stack AI Engineer
Handshaik
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Job Description
Handshaik is transforming how deals get done, trusted by leading industry organizations and fueled by a £1.7m pre-seed raise. They are building the AI platform of choice for modern dealmakers, as a fast-growing start-up where ideas move quickly from concept to product. The technology spans backend, frontend, data, and AI. As a Full Stack AI Engineer, you will work within the development team to help shape the technical vision. This hands-on role requires deep technical expertise and the ability to create a scalable solution, from prototype to production. You'll have the opportunity to build the product from the early stages, solving real customer problems, and playing a key role in the company’s journey. Responsibilities include building reliable backend APIs (Python/FastAPI), designing RAG & vector search pipelines, integrating OpenAI/Bedrock models, building data pipelines (Postgres/NoSQL), shipping fast UIs (React/Next.js), and evolving a modular platform (ECS on AWS). The role involves ensuring quality & reliability (testing, CI/CD, observability) and collaborating with Product and ELT teams. It's a great opportunity to contribute to technical strategy and research, with scope to shape the future of the product and the company itself.
Responsibilities
- Build reliable, secure services that power AI features and data retrieval at scale
- Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops)
- Own pgvector/Vector DB schemas, latency, relevance and cost
- Integrate OpenAI/Bedrock models, prompt/response orchestration, tool use, guardrails, and evaluation
- Ingest and transform structured/unstructured data; design efficient schemas (Postgres/NoSQL) to support retrieval and analytics
- Ship fast, accessible UIs that expose AI features clearly (search, filters, explanations, citations)
- Evolve a modular, scalable platform (ECS on AWS), with clear boundaries between ingestion, retrieval, reasoning and delivery
- Testing (unit/integration/evals), CI/CD, observability (tracing/metrics for LLM and retrieval paths), and performance tuning
- Work closely with Product and ELT; mentor engineers; contribute to technical strategy and research
- Research and recommend new tools, frameworks, and approaches for full-stack and AI development
Requirements
- 5+ years of professional experience in full-stack development
- Hands-on experience with RAG systems, vector databases (pgvector/FAISS/Weaviate/ES k-NN), embeddings, and hybrid search (BM25 + vectors)
- Strong grasp of chunking strategies, metadata, indexing, recall/precision trade-offs, reranking, and evaluation (ground-truth sets, offline/online metrics)
- Strong proficiency in Python (FastAPI) and React/Next.js
- Solid experience with SQL and NoSQL databases (e.g., Postgres, DynamoDB)
- Experience working with AI/ML models and APIs (LLMs, embeddings, vector search)
- Strong understanding of data engineering practices (ETL, schema design, performance tuning)
- Proficiency in cloud environments (AWS preferred) and containerised deployments (Docker, ECS)
- Strong grasp of secure coding practices and handling of sensitive data
- Excellent communication, problem-solving, and leadership skills
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