• Build a SRE team, from scratch. Hire experienced site reliability staff and build a team of 4-6 in year one. • Professionalize incident management. Define and document incident processes and practices for your SRE team and for the application feature teams. • Drive incident professionalism and reliability culture across the engineering organization through training and process adoption. • Use design reviews, code reviews, and blameless retrospectives to drive a culture of quality and excellence in engineering. • Balance incident response while also executing on a roadmap of observability and reliability engineering initiatives. • Hire and directly manage site reliability engineers. • Responsible for recruiting, onboarding, mentoring, coaching, and developing your team. • Recognizing and retaining high performers. • Leading horizontally with peer management & senior leaders.

Role Description As a Software Engineer on the Marketplace team, you’ll work at the intersection of full-stack product engineering and machine learning operations—helping power the systems that match renters to homes across ApartmentList.com, Kaleno.com and Sunny.com. You’ll contribute to a range of work: - Building and maintaining the backend which powers search - Supporting ML pipelines and model serving infrastructure - Collaborating closely with data scientists and engineers to bring ML capabilities into production This is a blended role for an engineer who is comfortable context-switching between product feature work and ML infrastructure, and who is excited to grow their depth in both areas. You’ll work closely with your Engineering Manager, product partners, and a globally distributed team. Qualifications - 5+ years of professional software engineering or ML Ops experience, with meaningful work in backend or full-stack development - Proficiency in at least one backend language (We use Ruby/Javascript, Go, Python) - Exposure to ML concepts and an interest in working at the boundary of software engineering and machine learning - Hands-on experience with ML Ops tooling—Vertex AI, MLflow, Kubeflow, or similar - Demonstrated proficiency managing data using SQL and programming languages, with exposure to feature pipelines and A/B testing frameworks - Experience with a balanced approach using AI tools – improving workflows, reducing feedback loops - Experience working in cloud environments (GCP preferred; AWS or Azure also considered) - Excellent communication skills as well as debugging instincts with an ownership mindset - Ability to collaborate effectively across time zones and with cross-functional partners Requirements - Mentorship experience for other engineers (Nice to Have) - Experience with search or recommendation systems (Nice to Have) - Experience working in an online marketplace (Nice to Have) - Familiarity with real-time systems, particularly in the context of optimizing latency and performance (Nice to Have) - Hands-on experience with feature stores — Chalk or similar (Nice to Have) Benefits - Compensation range based on experience and location - Zone 1: $144,000 - $174,000 TTC (including $129,000 - $153,000 base salary) + equity - Zone 2: $129,000 - $157,000 TTC (including $116,000 - $138,000 base salary) + equity - Consideration of market indicators, work location, job-related skills, experience, and relevant education and training for fair compensation - Potential for higher compensation in exceptional circumstances

• Design UX flows and interfaces for DBeaver desktop products • Analyze existing functionality and find weak points in the user experience • Work closely with developer team and product managers • Improve usability of technically complex workflows • Participate in product discovery and feature planning • Conduct UX research and collect feedback from technical users • Maintain consistency across desktop product experiences

CAPCO POLAND *We are looking for Poland based candidate. At Capco Poland, we’re not just another consultancy - we’re the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we thrive on helping clients tackle the toughest challenges across banking, payments, capital markets, wealth, and asset management. Help build and operate resilient cloud platforms supporting business-critical digital services for a leading global financial services organisation. We're looking for experienced Site Reliability Engineers to provide services supporting reliable, scalable and secure cloud platform services within a large-scale banking environment. Working alongside engineers, platform specialists and client teams, you'll help improve platform reliability, automate operational processes and strengthen production resilience across critical services. You'll also embrace AI-enabled ways of working, using approved automation and AI tools where appropriate to improve productivity while applying sound engineering judgement and responsible AI practices. What You'll Do - Deliver reliable, scalable Kubernetes-based platform services, improving availability, resilience and operational excellence. - Develop automation to simplify operational processes, reduce manual effort and improve service reliability. - Coordinate production support activities, including participation in agreed operational support arrangements, incident response, root cause analysis and continuous service improvement. - Build and enhance monitoring, alerting and observability using Grafana, Prometheus and related tooling to proactively identify and resolve issues. - Collaborate with engineering teams to enhance CI/CD pipelines, platform automation and AI-enabled operational workflows, applying appropriate governance, human oversight and engineering judgement. What We're Looking For - 5+ years of experience in relevant position supporting banking or other highly regulated environments. - Strong programming skills in Python, Java or Go, with experience developing automation and operational tooling. - Hands-on experience with Kubernetes in production environments. - Strong experience with monitoring and observability tools such as Grafana and Prometheus. - Experience with CI/CD technologies such as Jenkins and infrastructure automation using Terraform. - Experience working with AWS or Google Cloud Platform (GCP). - Exposure to AIOps platforms or intelligent operational automation. - A collaborative approach with an interest in using approved AI tools and automation to improve delivery while maintaining quality, security and responsible AI standards. - Familiarity with platform engineering practices supporting AI or machine learning workloads. - Experience delivering services in production environments requiring continuous (24x7) operational support. We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on diverse projects. Recruitment Process: - HR Interview with the recruiter - Technical Interview - Client Interview - Feedback and offer #LI-HYBRID