Agile Lab

• Coordinate team activities , priorities, and task ownership, ensuring effective delivery. • Support troubleshooting, incident resolution, and escalations across microservices and distributed systems. • Maintain and improve the reliability and performance of applications running on OpenShift. • Contribute to monitoring, observability, alerting, and post-incident improvement actions. • Identify opportunities to automate recurring activities and simplify operational processes. • Work with customers and technical stakeholders to understand priorities and business impact. • Promote accountability, collaboration, and engineering best practices within the team.

• Ensure high reliability of microservices running in OpenShift / Kubernetes environments • Lead and coordinate a technical team of 3–4 engineers for operational excellence • Manage incident resolution and ticketing workflows via ServiceNow • Collaborate with development teams to drive performance optimization and tuning • Design, configure and maintain monitoring dashboards (Grafana, Prometheus, etc.) • Coordinate with Service Control Room to maintain effective alerting and response • Oversee release processes of new features, hotfixes, and updates in production

• Manage enterprise storage on Hitachi VSP Gx00 and 5x00 , covering LUN and volume provisioning, troubleshooting, and replication with GAD, UR, and SI • Storage NetApp AFF and FAS , deliver SAN and NAS services, oversee provisioning and health, resolve issues, and configure SnapMirror replication • Handle Purestorage X90 for day to day management, provisioning, and incident resolution • Operate Brocade GEN5 and later switches and directors, performing zoning, pathing, and diagnostics • Use Hitachi OPS Center to monitor Hitachi arrays and analyze performance, NetApp Active IQ Unified Manager to track NetApp health and capacity, and Brocade BNA to administer Brocade fabrics and report on events and performance

• Guide installation and configuration of Witboost in the customer's environment, working alongside their platform team to tailor deployment architecture and resolve technical blockers • Run onboarding and training sessions for platform teams and key stakeholders, ensuring they understand the platform's concepts, templates, policies, and capabilities • Drive Playground and MVP phases to demonstrate value quickly and build internal champions within the customer's organization • Own the Time to First User metric, proactively removing friction and ensuring every prerequisite for production readiness is met (templates, policies, RBAC, custom views, data contracts, access flows) • Conduct regular check-ins (bi-weekly syncs, quarterly reviews) to track adoption, health scores, and open issues • Communicate new releases proactively, highlighting relevant features and running mini-demos to drive upgrade adoption • Act as the voice of the customer internally — feeding real-world feedback, unmet needs and feature gaps to Product Management to shape the roadmap • Spot expansion opportunities and flag them to Sales early, supporting renewal conversations with adoption data and business impact evidence • Uncover root causes, not just requests — when a customer asks for a feature, dig for the underlying problem and bring the real insight back to Product

• Actively collaborate with business stakeholders to understand and translate functional requirements into technical specifications, ensuring proper implementation of use cases • Data flow implementation: design and implement new data flows on EDWH or Data Lake to meet specific business requirements, identifying and integrating necessary data sources • Data cleaning and preparation: conduct data preparation and cleaning activities to ensure the quality and reliability of the data used in analyses • Data quality techniques implementation: apply techniques and processes to ensure data integrity and reliability through quality control • Data model creation: develop specific data models for identified use cases, transforming input data into formats suitable for analysis and insight generation • Collaboration with dashboarding experts: work closely with dashboarding and data visualization experts to implement effective dashboards and reporting, presenting results in a clear and engaging manner

• Analyzes, designs, and implements complex systems • Challenges the team processes, looking for ways to improve • Mentors junior engineers via pairing, design, and code review • Builds software solutions by adhering to our quality standards about SDLC • Makes active efforts to stay up-to-date with technologies • Leads the technical design of complex systems • Understands and optimizes system performances • Takes the initiative to fix issues before they become a problem • Delivers complex systems, well-baked, and almost bug-free • Proactively identifies problems with requirements and project plan.

• Defining and driving the technical vision and strategy for Generative AI initiatives across projects and teams • Acting as a senior technical authority on GenAI system design, agentic architectures, observability, and production readiness • Advising multiple teams on architectural decisions, trade-offs, and best practices for ML and GenAI solutions • Overseeing the design and evolution of scalable, secure, and maintainable AI platforms • Leading and supporting pre-sales and client-facing activities: Conducting technical discovery and solution design; Assessing feasibility and analyzing risks; Contributing to proposals and delivering technical presentations • Managing stakeholders effectively in complex and ambiguous environments • Mentoring both senior and junior team members, fostering technical excellence and leadership development • Collaborating with leadership to evolve processes, standards, and organizational capabilities • Anticipating technological trends and identifying opportunities for innovation and continuous improvement

• Build and operate modern AI systems in production • Help build an AI Operating System: a harness‑centric runtime that turns powerful foundation models into reliable, long‑running systems • Provide structured capabilities—tool and filesystem access, code‑as‑action execution, skills loaded on demand, semantic grounding via knowledge graphs and ontologies, sub‑agent delegation, memory, and built‑in evaluation loops • Enable declarative agent design, where behavior emerges from clearly defined capabilities, constraints, and feedback • Model and leverage semantic layers across data and services: Knowledge graphs and entity relationships • Integrate semantic systems with retrieval and agentic workflows to support grounded answers, better contextualization, traceability • Build production-grade backend services and APIs that expose AI capabilities • Contribute hands-on to implementation, architecture, and engineering standards: Clean architecture, modular design, testing strategies • Evaluate new AI technologies quickly, understanding: when to adopt, when to wait, and how to mitigate risks • Collaborate with product, platform, and data teams to translate requirements into architecture decisions, delivery plans, measurable outcomes and quality gates • Produce high-quality technical documentation and architecture artifacts • Help teams and stakeholders navigate complexity with clear technical thinking and pragmatic choices • Make technical decisions under uncertainty and iterate safely, using experimentation and fast feedback loops, observability and measurable outcomes, fallback and rollback strategies

• Analyzes, designs, and implements complex systems • Challenges the team processes, looking for ways to improve • Mentors junior engineers via pairing, design, and code review • Builds software solutions by adhering to our quality standards about SDLC • Makes active efforts to stay up-to-date with technologies • Leads the technical design of complex systems • Understands and optimizes system performances • Takes the initiative to fix issues before they become a problem • Delivers complex systems, well-baked, and almost bug-free • Proactively Identifies problems with requirements and project plan • Go to an expert in one technological area • Research and propose new technologies • Detect possible performance bottlenecks • Known for drama-free launches • Can jump into an old project and fix it • Consistently influence technical and business roadmap of services/products/projects • Proactively identify and tackle tech debt • Communicate with self-awareness • When proposing something, at any level, is doing it in written form and providing the proper context • Contributes to the career development of others.

• Analyzes and implements a complex feature autonomously; • Builds software solutions by adhering to our quality standards about SDLC; • Participates in the technical design of features with guidance; • Understands and optimizes system performances; • Prioritizes tasks with autonomy based on requirements and proper context.