Senior Product Manager (LLM Inference)

Location: Remote, United Kingdom

Company

hirify.global provides an on-demand Model API and dedicated inference solutions for LLM workloads.

What you will do

• Own the LLM inference strategy, roadmap, model catalog, lifecycle, and commercial outcomes.
• Lead customer discovery with developers, AI teams, and technical decision-makers to identify production workloads, adoption barriers, and product-market fit.
• Shape developer-facing API capabilities, SDKs, documentation, compatibility, streaming, tool calling, structured outputs, caching, and batch inference.
• Partner with Engineering on latency, time to first token, throughput, concurrency, availability, routing, fallbacks, observability, dedicated capacity, and serving efficiency.
• Drive pricing, packaging, positioning, technical evaluations, production adoption, retention, expansion, revenue, gross margin, and service quality.
• Define enterprise capabilities for data residency, retention controls, security, service commitments, and other production requirements while writing requirements, prototyping, testing APIs, and resolving technical constraints.

Requirements

• Proven ownership of technically complex, developer-facing products such as API products, developer platforms, AI infrastructure, or similar offerings from strategy and development through launch, adoption, and commercial growth.
• Strong understanding of production LLM inference, including model capabilities, output quality, context length, token consumption, latency, throughput, reliability, cost, and serving trade-offs.
• Deep understanding of developer experience and API products, including integration, production scaling, API design, compatibility, migration, SDKs, documentation, and model capability differences.
• Strong commercial and product judgment for balancing customer requirements, technical constraints, market opportunities, pricing, and unit economics.
• Experience working directly with technical customers, leading discovery, evaluating production use cases, and distinguishing recurring market needs from isolated requests.
• Hands-on technical aptitude with API testing, product exploration, usage-data analysis, prototyping, and implementation discussions with engineers.
• Strong execution and cross-functional leadership, including navigating ambiguity, communicating decisions, aligning stakeholders, and owning measurable outcomes from discovery through delivery.

Nice to have

• Direct experience building or scaling an LLM inference API, model-serving platform, or AI infrastructure product.
• Knowledge of GPU inference and model-serving technologies, including batching, quantization, KV caching, capacity planning, vLLM, SGLang, or TensorRT-LLM.
• Experience with LLM evaluation, benchmarking, and production applications such as AI agents, coding assistants, or retrieval-augmented generation systems.
• Experience with usage-based pricing, token metering, billing systems, inference unit economics, or dedicated capacity commitments.
• Familiarity with enterprise data security, residency, observability, and service reliability requirements.
• Hands-on experience in software engineering, machine learning engineering, infrastructure, or developer tooling.

Culture & Benefits

• Remote-first work with in-person meetings twice a year for planning, brainstorming, and team connection.
• Core collaboration hours with flexible scheduling outside those hours.
• Fast, intense release cycles followed by expected downtime and recovery.
• Paid vacation, sick days, public holidays, maternity, paternity, and caregiver leave.
• Meaningful stock options and twice-yearly company retreats.