Tech Lead - Optimisation Engineering

We are easyJet – a FTSE-250 listed, £multi‑billion low‑cost airline that serves tens of millions of customers every single year. We fly more than 1,207 routes, connecting 38 countries across Europe, and employ more than 18,000 colleagues. We’re on a mission to make low‑cost travel easy – and whatever your role here, you’ll connect millions of people to what they love using Europe’s best airline network, great value fares, and friendly service.

Our Promise Behaviours – we are Safe, Bold, Welcoming and Challenging.

Role Summary

Lead a software engineering team building decision‑support products that solve complex disruption‑management and crew/roster optimisation challenges. Translate operational problems into scalable software and optimisation solutions, partnering closely with product, data/operations research (OR), and customer stakeholders. The role blends people leadership with hands‑on technical direction across architecture, delivery, quality, and reliability.

Key Responsibilities

• Lead, coach, and grow a cross‑functional team of software engineers (and closely partnered OR/data science specialists).
• Own technical direction and delivery for products that model, optimise, and operationalise solutions to disruption and crewing problems (e.g., recovery planning, re‑optimisation, what‑if analysis).
• Drive architecture and design decisions for services, APIs, data pipelines, and user‑facing workflows that support optimisation at scale.
• Partner with product management to shape roadmap, break down ambiguous problem statements, and define measurable outcomes and acceptance criteria.
• Collaborate with OR/optimisation experts to integrate solvers (e.g., Gurobi) and ensure model performance, correctness, explainability, and maintainability.
• Establish strong engineering practices: code review, automated testing, CI/CD, release management, incident response, and post‑incident learning.
• Build observability into optimisation services (KPIs, logs, traces) and manage performance tuning (latency, throughput, cost) across environments.
• Contribute hands‑on when needed (prototyping, critical‑path coding, reviews), while primarily enabling the team to deliver consistently.

Required Qualifications

• Proven experience leading a software engineering team delivering production‑grade systems (people leadership and/or strong technical leadership), that encompass solver technology (like CPLEX or Gurobi).
• Strong software engineering fundamentals: system design, distributed systems concepts, APIs, data modelling, testing, and operational excellence.
• Experience building optimisation, scheduling, or decision‑support applications, or closely related domains requiring complex constraint‑based reasoning.
• Working knowledge of mathematical optimisation concepts (e.g., MILP, constraint programming, heuristics/metaheuristics) and how they impact product design.
• Hands‑on programming experience in one or more mainstream languages (e.g., Python, Java, C#, C++), with the ability to review and guide code quality.
• Experience integrating and operating optimisation components (e.g., solver orchestration, model/service boundaries, runtime configuration, fallbacks).
• Ability to communicate clearly with both technical and non‑technical stakeholders, and to translate operational needs into engineering deliverables.

Preferred Qualifications

• Deep experience with commercial optimisation solvers (e.g., Gurobi), including parameter tuning, licensing/packaging considerations, and performance troubleshooting.
• Experience in airline/rail/transport operations, logistics, workforce management, or similar disruption/crew scheduling environments.
• Familiarity with simulation and scenario generation to support what‑if analysis and resilience planning.
• Experience designing human‑in‑the‑loop decision tools (explainability, constraints override, auditability, and traceable recommendations).
• Cloud platform experience (Azure/AWS/GCP) and building secure, scalable services.
• Experience with event‑driven architectures, streaming, and near‑real‑time optimisation.
• Experience with data science/ML components that complement optimisation (forecasting, demand estimation, delay prediction).

Technical Skills & Tools

• Optimisation: Gurobi (or equivalent), model libraries/APIs, batching/warm starts, parameter management, sensitivity analysis.
• Languages: Python and/or Java/C#/C++ (based on team stack).
• Services: REST/gRPC APIs, microservices and/or modular monoliths, asynchronous job orchestration.
• Data: SQL, data pipelines/ETL/ELT, caching strategies, data quality checks, reproducible inputs/outputs.
• DevOps: CI/CD, infrastructure as code, containerisation (e.g., Docker), monitoring/alerting, incident management.
• Quality: unit/integration tests, performance tests, model validation frameworks, feature flags.

Location & Hours of Work

We operate a hybrid working policy of 40‑60% of the month spent with colleagues.

Reasonable Adjustments

At easyJet, we are dedicated to fostering an inclusive workplace that reflects the diverse customers we serve across Europe. We welcome candidates from all backgrounds. If you require specific adjustments or support during the application or recruitment process, such as extra time for assessments or accessible interview locations, please contact us at ma.recruitment@easyjet.com. We are committed to providing reasonable adjustments throughout the recruitment process to ensure accessibility and accommodation.

Benefits

• Competitive base salary
• Annual bonus
• 25 days holiday, pension scheme, life assurance, and a flexible benefits package.
• Discounted staff travel scheme for friends and family
• Annual credit for discount on easyJet holidays
• ‘Work Away’ scheme, allowing you to work abroad for 30 days a year
• Electric vehicle lease salary sacrifice scheme