Engineering Lead

Job Title: Engineering Lead Job Location: Poland, Remote Job Type: Contract Job Description : Position Summary: The Engineering Lead is responsible for leading the design, development, delivery, and operational excellence of a cloud-native enterprise software product running on Microsoft Azure. This role provides technical leadership to cross-functional engineering teams, establishes engineering standards and architecture guardrails, and ensures delivery of scalable, secure, reliable, and AI-enabled solutions. The Engineering Lead partners closely with Product Management, Solution Architecture, DevOps, Security, UX, Data, and AI engineering teams to deliver innovative software capabilities that create measurable business value. The role combines hands-on technical leadership with people leadership, mentoring, and strategic technology planning. Key Responsibilities: Technical Leadership Own the overall technical delivery of one or more product domains.Lead architecture and design decisions for cloud-native solutions running on Microsoft Azure. Ensure adherence to engineering standards, security requirements, and enterprisearchitecture principles. Drive software quality through code reviews, design reviews, testing strategies, and engineering best practices.Provide technical guidance and mentorship to development teams Product Delivery Collaborate with Product Managers and Architects to translate business requirements into scalable technical solutions.Lead sprint planning, backlog refinement, estimation, and execution activities.Identify and mitigate technical risks and delivery dependencies.Drive successful delivery of product releases while balancing quality, cost, and schedule. Cloud Engineering & Operations Lead development of microservices, APIs, event-driven architectures, and distributed systemsEnsure solutions are designed for reliability, availability, scalability, and observability.Partner with DevOps teams to implement CI/CD pipelines and infrastructure automation.Monitor platform health, performance, security, and operational metrics. AI and Intelligent Solutions Drive adoption of AI capabilities within products and engineering practices.Evaluate opportunities to leverage Generative AI, AI Agents, Retrieval-Augmented Generation (RAG), Copilot technologies, and machine learning services.Guide implementation of Azure AI services, agent frameworks, vector databases, AI search, and intelligent workflow automation.Establish responsible AI practices including governance, security, transparency, testing, and compliance.Promote AI-assisted engineering practices to improve developer productivity and software quality. Team Leadership Build, mentor, and develop high-performing engineering teams.Foster a culture of accountability, innovation, collaboration, and continuous improvement.Support hiring, onboarding, performance development, and career growth of engineers.Encourage knowledge sharing and engineering excellence across teams. Stakeholder Management Partner with business stakeholders, product leaders, and technology leadership.Communicate technical direction, delivery plans, risks, and status effectively.Influence strategic technology decisions and roadmap planning Required Qualifications Education Bachelor's degree in Computer Science, Software Engineering, Information Technology, or related fieldMaster's degree preferred. Experience 10+ years of professional software development experience.3+ years leading software engineering teams.Proven experience delivering enterprise-scale software products.Experience operating mission-critical applications in cloud environments. Technical Skills Software Development Strong proficiency in one or more modern programming languages such as:◦ C# ◦ Java ◦ TypeScript Python Experience with API design and microservices architecture.Knowledge of modern software design patterns and distributed systems. Microsoft Azure Hands-on experience with Azure services including:◦ Azure App Services ◦ Azure Functions ◦ Azure Kubernetes Service (AKS) ◦ Azure Container Registry ◦ Azure API Management ◦ Azure Storage ◦ Azure SQL Database ◦ Azure Cosmos DB ◦ Azure Service Bus/Event Grid ◦ Azure Monitor and Application Insights ◦ Azure DevOps and GitHub DevSecOps CI/CD automationInfrastructure as Code (Terraform, Bicep, ARM)Security-by-design principlesAutomated testing and deployment practicesCloud observability and monitoring AI & Data Working knowledge of: Generative AI concepts and architecturesLarge Language Models (LLMs)Prompt engineeringRetrieval-Augmented Generation (RAG)AI Agent architecturesAzure AI ServicesAzure AI SearchAzure OpenAI ServiceVector databases and semantic searchResponsible AI principles and governanceAI evaluation and monitoring techniques Leadership Competencies Strategic thinking Technical decision makingInfluencing without authorityTeam development and coachingContinuous improvement mindsetCustomer-centric deliveryStrong communication skillsCross-functional collaboration Success Measures Predictable and high-quality delivery of product roadmap commitmentsPlatform reliability, security, and performance targets achievedEngineering productivity and velocity improvementsReduced technical debt and improved architecture maturitySuccessful integration of AI capabilities into products and engineering processesHigh employee engagement, retention, and growth within engineering teamsStrong stakeholder satisfaction and business outcomes Preferred Certifications Microsoft Certified: Azure Solutions Architect ExpertMicrosoft Certified: Azure Developer AssociateMicrosoft Certified: Azure AI Engineer AssociateCertified Kubernetes Administrator (CKA)SAFe, Scrum, or Agile leadership certifications Ideal Candidate Profile A successful Engineering Lead combines the mindset of a software architect, the pragmatism of a delivery leader, and the curiosity of an AI innovator. They can lead teams building modern enterprise products on Azure while strategically incorporating AI capabilities to improve both customer experiences and engineering effectiveness.