Engineering Leader

• Architect and build multi-tenant systems that serve enterprise customers across geographies with strict data residency, isolation, and compliance requirements.

• Design high-throughput ingestion systems capable of processing large volumes of voice data, call metadata, and operational telemetry in near real-time.

• Make foundational architectural decisions on data stores, stream processing, and storage tiers — balancing query performance, cost, and operational simplicity.

• Champion SOLID principles, clean architecture, and engineering rigor across all codebases — ensuring systems are testable, extensible, and maintainable at scale.

• Recruit, hire, and develop senior engineers across a multi-disciplinary function spanning voice engineering, backend systems, data engineering, and applied operations research.

• Establish engineering standards, code review culture, and a strong bias toward shipping — with equal commitment to system reliability and customer experience.

• Coach and grow senior/staff engineers into technical leaders; manage engineering managers as the organization scales.

• Drive cross-functional alignment with Product, ML/AI, and Go-to-Market teams to ensure the platform evolves in lockstep with customer needs and market feedback.

• Own the end-to-end engineering for Ema’s AgentQA capabilities — real-time voice pipelines, telephony integrations, and voice-to-action workflows.

• Build and scale the Agent QA platform: automated call scoring, compliance monitoring, sentiment analysis, and coaching feedback loops.

• Design auto-learning systems that continuously improve voice agents from production interactions — closed-loop feedback, model retraining triggers, and quality regression detection.

• Deliver rich voice analytics: call volume trends, handle time distributions, first-call resolution metrics, agent performance dashboards, and anomaly detection.

• Build scalable voice pipeline across geographies – keeping in mind PII, security and compliance requirements.

• Build WFM capabilities including demand forecasting, shift scheduling, real-time adherence monitoring, and capacity planning — applying operations research techniques to optimize workforce utilization.

• Design and implement optimization algorithms for headcount modeling, skill-based routing, and workload balancing across multi-site, multi-timezone contact center operations.

• Partner with ML/AI teams to integrate predictive models for call volume forecasting, attrition risk, and staffing efficiency.

• 12+ years of software engineering experience, with 4+ years leading engineering teams of 8+ engineers at high-growth startups or top-tier tech companies.

• Deep expertise in building real-time, data-intensive systems.

• Strong foundation in data stores and storage systems: relational databases, time-series stores, columnar analytics engines, and caching layers — with the judgment to choose the right tool for the workload.

• Experience building quality software using AI-driven tools and workflows.

• Track record of taking products from 0→1 and iterating rapidly based on customer feedback.

• Hands-on proficiency with SOLID principles, clean architecture, and design patterns — you write and review production code and lead by example on system design.

• Experience building scalable multi-tenant SaaS platforms with data isolation, geo-distributed deployments, and compliance requirements (SOC 2, GDPR, HIPAA).

• Track record of building ingestion systems for high volumes of load — event-driven architectures, stream processing (Kafka, Flink, or equivalent), and batch/real-time hybrid pipelines.

• Strong product sense: ability to deeply understand customer problems in contact center, voice, and workforce domains and translate them into clean technical solutions.

• Proven ability to hire, develop, and retain high-caliber engineers across multiple disciplines in competitive markets.

• Experience in voice/telephony systems: WebRTC, SIP, voice-over-IP infrastructure, or contact center platforms.

• Background in operations research or optimization: scheduling algorithms, linear/integer programming, constraint satisfaction, or demand forecasting models.

• Experience building analytics platforms: OLAP systems, real-time dashboards, metric computation engines, or BI infrastructure.

• Prior work on auto-learning or continuous improvement systems: feedback loops from production data, automated retraining pipelines, or quality monitoring systems.

• Experience with AI/ML-powered products in enterprise settings — agentic automation, LLM orchestration, or AI-driven UX.

• Familiarity with WFM or contact center operations — staffing models, Erlang-based capacity planning, or real-time adherence systems.

• Build at the intersection of Voice AI, operations research, and enterprise-scale systems — a rare combination of deeply technical challenges with direct customer impact.

• Shape the engineering foundation of a category-defining AI platform — your architectural decisions will power how the world’s largest enterprises run their voice and workforce operations.

• High-impact, high-visibility role with direct access to the Head of Engineering, co-founders, and enterprise customers.

• A team of exceptional engineers from Google, Meta, Microsoft Research, and top CS programs worldwide.

• Competitive compensation, meaningful equity, and the opportunity to build something that matters.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics. Find Jobs in United Kingdom on Arbeitnow