Distyl AI

Supports the CEO by managing complex logistics, stakeholder relationships, follow-through, and ambiguous business projects while improving Office of the CEO systems. Requires 0–3 years of experience, exceptional organization and judgment, strong communication, and comfort using AI tools.

Own end-to-end delivery of complex AI implementation programs for UK enterprise clients, coordinating technical teams, executives, budgets, risks, and measurable outcomes. The role requires large-scale enterprise delivery experience, operational rigor, strong communication, AI fluency, and substantial UK travel.

Build and lead Distyl's Talent Acquisition function to scale headcount with high-quality AI-native hires during rapid growth. Own strategy, team, processes, ATS, metrics, and international expansion while partnering on headcount planning and defining emerging AI roles.

Lead AI Strategist partnering with CIOs and COOs at large enterprises to reshape operations with AI. Requires 10-15+ years advising executives on technology and business strategy, deep enterprise transformation experience, and AI fluency to drive $100M+ value programs.

Research Engineers at Distyl build and productionize post-training techniques (fine-tuning, RLHF, reward models, evals) to improve reliability and behavior of compound AI systems for enterprise customers. Requires strong applied ML experimentation skills and ownership of real-world outcomes.

Research Engineers at Distyl build and productionize reliable agentic AI systems and compound architectures for enterprise workflows. They design agents, develop evaluation frameworks, run experiments on reasoning and failure modes, and integrate into customer environments.

Research Engineers at Distyl build data systems and pipelines that power reliable compound AI workflows in enterprise environments. They create data quality frameworks, synthetic data strategies, and evaluation tools while partnering with researchers and customers to turn raw data into production AI value.

Senior technical leader accountable for complex enterprise AI deployments. Owns technical direction across multi-team engagements, develops engineering leaders, and partners with customer executives on architecture and delivery.

Lead Forward Deployed AI Engineer owning architecture, execution, and delivery of production AI systems for enterprise customers. Hands-on technical leader mentoring engineers, integrating AI into customer platforms, and iterating on live systems.

Design and implement evaluation frameworks and pipelines for AI systems using Evaluation-Driven Development. Build Python-based test suites, LLM graders, and measurement systems that guide prompt iteration and production deployment decisions.

Forward Deployed AI Engineer building and operating production AI systems in customer environments. Requires 2+ years software engineering experience, hands-on LLM/AI system building, strong Python fundamentals, and willingness to travel 10-30%.

Leads end-to-end AI engagements for enterprise customers, from discovery and solution scoping through delivery, adoption, and measurable business impact. The role combines client leadership, product judgment, enterprise data analysis, and coordination of engineering and research teams, with significant travel.

Build and deploy production-grade LLM applications and AI agents for enterprise customers, from architecture through production. The role requires at least three years of software engineering experience, strong Python or TypeScript skills, and hands-on experience with AI workflows and production systems.

Develop multi-agent AI architectures for enterprise coordination and collaborative reasoning. Requires research experience in MARL/GNNs, strong prototyping skills, and daily AI tool usage.

Leads AI solutioning and GTM for healthcare clients, diagnosing problems through an AI lens, building demos/POCs on Distillery platform, and driving deals from discovery to close. Requires 8-12 years experience in sales engineering/solutions consulting with deep healthcare domain knowledge and hands-on GenAI skills.

AI Operator enforces operational rigor, drives stakeholder alignment, and accelerates execution across revenue, platform delivery, or research programs at a high-velocity AI company. Thrives in chaos, uses frontier AI tools daily, and owns outcomes from ambiguity with ~20% travel.

Leads end-to-end delivery of complex AI implementations for Fortune 500 clients, managing workstreams, enforcing operational rigor, and driving stakeholder alignment with 25-50% travel. Requires enterprise-scale execution experience, AI-native mindset, and comfort in high-pressure environments.

Builds and scales AI-native backend infrastructure and cloud-native microservices using Python and Kubernetes for enterprise AI workflows. Requires 3+ years backend experience with cloud platforms and DevOps tools.

Technical growth leader opening new vertical markets by building outbound pipeline, running discovery with enterprise buyers, closing design partners, and shaping AI platform solutions. Requires 5-10 years technical BD/sales experience and fluency in AI architectures.

Owns strategic enterprise healthcare accounts, leading complex sales cycles for AI-driven solutions like prior authorization automation and clinical workflow orchestration. Targets senior executives in payers/providers with 8-12+ years enterprise sales experience closing $1M+ deals.

Leads AI projects for enterprise customers, owning end-to-end engagements from problem identification and workflow embedding to delivery, user adoption, and iteration. Requires client-facing experience, leadership, user empathy, and coding proficiency in Python/SQL.

Applied AI Researcher on System Discovery team explores new AI system architectures, prototypes human-AI collaborations, and draws cross-domain insights to redefine enterprise workflows. Requires proven research track record, expertise in compound AI systems and agentic techniques, strong programming for rapid prototyping.

Designs self-constructing AI systems that autonomously generate, assemble, and refine subsystems using meta-learning, program synthesis, and evolutionary methods. Requires proven research in modular AI architectures, daily AI tool usage, and strong prototyping skills.

Designs feedback-driven AI architectures for system self-improvement, enabling autonomous evolution through reflection, retraining, and adaptation. Requires proven research in compound AI systems, daily AI tool usage, and strong prototyping skills.

Designs and researches compound AI systems integrating LLMs, agents, and execution components for reliable enterprise workflows. Requires proven AI research track record, daily AI tool usage, strong prototyping skills, and expertise in agentic techniques.

Develops and evaluates post-training techniques like supervised fine-tuning, RLHF/DPO, and continual adaptation to align foundation models with enterprise systems. Requires expertise in adapting LLMs/SLMs, compound AI systems, and strong prototyping skills.

Designs and constructs AI benchmarks and evaluation frameworks to measure reasoning, reliability, and real-world impact of intelligent systems. Requires experience with model evaluations, statistical rigor, building with AI models, and strong programming for prototypes.