Job Description

800 per day, outside IR35

Flexible with days/hours

Remote working

Creativity, leadership, and autonomy to lead on ideas

Start-up business

Hive Technologies is developing a next-generation multi-domain analytics and data-fusion platform designed for defence, security, and intelligence environments.

We are seeking a Senior AI / LLM Engineer with deep expertise in Kotlin, AI/ML systems, and edge-deployed architectures to help close key capability gaps in the defence sector's use of real-time AI and data integration!

You will design, develop, and operationalise large language models (LLMs), multi-modal fusion pipelines, and real-time analytics algorithms deployable on distributed edge devices, drones, and tactical networks. The ideal candidate combines AI research expertise with high-reliability software engineering across both Python and Kotlin ecosystems.

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Key Responsibilities

Architect, fine-tune, and deploy LLM and generative-AI systems customised for defence workflows -- including summarisation, intelligence fusion, and autonomous decision-support. Develop and optimise multi-modal data-fusion pipelines combining imagery, signal, geospatial, and textual data into coherent situational awareness models. Build real-time, event-sourced data frameworks in Kotlin (e.g. Ktor, Kafka Streams, Axon) to orchestrate sensor, telemetry, and mission data. Integrate Python-based AI models with Kotlin back-end services, enabling low-latency inference across tactical edge nodes and command networks. Implement retrieval-augmented generation (RAG), vector embeddings, and knowledge-graph systems to enable context-aware reasoning across distributed domains. Design streaming ingestion and event-correlation layers using Kotlin coroutines, reactive Flows, and asynchronous I/O for high-throughput telemetry fusion. Deploy lightweight AI inference on constrained hardware (embedded GPUs, NPUs, CPUs) via ONNX, TensorRT, or Kotlin-Native modules. Lead experiments, demonstrations, and customer pilots showcasing cross-domain AI capabilities and digital-twin scenarios. Apply MLOps practices -- containerisation (Docker/K8s), model tracking (MLFlow), continuous delivery, monitoring, and versioning for operational AI systems. Ensure security, explainability, and resilience of deployed models under adversarial or degraded network conditions.
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Required Skills & Experience

Programming & Systems

Expert in Kotlin for event-sourced, multi-domain, and real-time application development. Experience in Python for AI/ML model development, data-science pipelines, and experimentation. Proven experience integrating Kotlin back-end services with Python inference engines via REST/gRPC/messaging interfaces. Knowledge of coroutines, Flow, asynchronous orchestration, and reactive architectures. Experience with streaming data frameworks (Kafka, Pulsar, Akka Streams) and CQRS/event-driven design. Proficient in containerisation (Docker/Kubernetes), CI/CD, and secure data exchange protocols (MQTT, AMQP, ZeroMQ).
AI / ML / LLM Expertise

Deep understanding of transformer architectures, LLM fine-tuning (LoRA, RLHF, adapters), and quantisation. Hands-on with PyTorch, JAX/Flax, TensorFlow, and Hugging Face Transformers. Experience building retrieval-augmented generation pipelines, embedding stores, and vector databases (e.g. Milvus, Qdrant, Pinecone). Experience integrating multi-modal models (text, vision, signals) for fusion and decision support. Strong grounding in MLOps, model lifecycle management, monitoring, and edge deployment optimisation.
Domain Knowledge

Understanding of defence, ISR, C2, EW, GEOINT, and multi-domain operations. Familiarity with edge-deployment constraints: bandwidth, compute, security, and connectivity limitations. Experience with data classification, security handling, encryption, and air-gapped environments.
Leadership & Delivery

5-8+ years of professional experience in AI/ML and advanced software engineering (preferably in defence, national security, or high-integrity systems). Strong architectural thinking and communication skills across technical and non-technical stakeholders. Demonstrated ability to deliver R&D concepts into operational prototypes and production-ready systems. Mentoring ability and commitment to cross-functional collaboration with hardware, data, and mission teams.
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Desirable / Differentiators

PhD or MSc in AI, ML, NLP, computer vision, or embedded systems. Experience with Kotlin Multiplatform / Kotlin-Native for edge AI. Familiarity with knowledge-graph and ontology engineering. Experience in digital twins, simulation, and synthetic data generation. Background in federated / distributed learning and on-device adaptation. Prior experience in classified or government R&D projects.
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Benefits & Culture

Work on frontier AI applications directly impacting national and allied defence capabilities. Competitive compensation, equity options, and professional-development pathways. Flexible working model (remote / hybrid / on-site depending on clearance). Collaborative, mission-driven culture combining innovation, rigour, and delivery focus.
Job Types: Part-time, Fixed term contract
Contract length: 12 months

Pay: 800.00 per day

Expected hours: 8 - 20 per week

Benefits:

Flexitime Work from home
Work Location: Remote