secure cloud development practices and IAM role design. · Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch). · Exposure to contact centre automation, conversational agents, or RAG pipelines. Please click here to find out more about our Key Information Documents. Please note that the documents provided contain generic information. If we are successful in finding you an More ❯
support secure, air-gapped AI deployments, with a focus on NLP-based tooling * Develop pipelines for transcription ingestion and real-time analytical insight generation * Support graph and RAG-based inference layers using data from structured and unstructured sources * Build and expose APIs for frontend consumption, enabling natural-language querying, dynamic visualisation, and reporting * Ensure system portability via containerisation More ❯
Doing: Architecting and implementing secure backend services to support AI deployments in classified settings Developing transcription ingestion pipelines and real-time insight generation capabilities Supporting graph and RAG-based inference pipelines using structured and unstructured data Exposing robust APIs for frontend engineers to deliver interactive dashboards and NLP-driven workflows Ensuring system portability via containerisation (Kubernetes, Docker) Collaborating … of Postgres or similar databases Proven experience building real-time or batch AI/ML pipelines with strong API design (Bonus) Exposure to LLMs, vector databases, transcription pipelines, or RAG systems (Bonus) Prior work in Defence, aerospace, or national security environments Why This Project? This isn’t another generic SaaS deployment. You’ll be building backend systems that enable critical More ❯
