Lingaro

Data Scientist

• Support build end‑to‑end GenAI applications such as chatbots, voicebots, Talk-to-Data systems, where you will help buiild: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed.
• Implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.
• Perform model selection, prompting strategies, and fine‑tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including guardrails, output evaluation and A/B testing.
• Integrating and optimizing LLMs interaction with external tools, APIs, and data sources in a standardized and scalable way by using Model Context Protocol (MCP) connectors
• Business understanding and translating problems into technical goals by defining tasks, auditing data feasibility, and highlighting issues.
• Supporting project delivery

Lead Data Scientist – Gen AI

QA Engineer

• Develop comprehensive test plans based on project requirements and specifications. Work with stakeholders to define testing scope, objectives, and strategies.
• Create detailed and effective test cases covering various scenarios, edge cases, and user workflows. Ensure test cases align with business requirements and acceptance criteria.
• Execute automated test cases to identify defects and ensure software functionality. Conduct regression testing to validate the stability of new features and updates.
• Develop and maintain automated test scripts to enhance testing efficiency. Identify opportunities for test automation and implement automation frameworks.
• Log, prioritize and track defects through their lifecycle. Work closely with development teams to investigate, reproduce, and resolve issues.
• Collaborate with developers, product managers, and other stakeholders to understand software requirements and user expectations. Provide feedback on the quality of deliverables and suggest improvements.
• Conduct performance testing to evaluate software performance under different conditions. Identify and address performance bottlenecks.
• Create and maintain clear and concise documentation of test plans, test cases, and testing processes.
• Contribute to the continuous improvement of QA processes and methodologies.

Quality Assurance Engineer

Recruitment

• Participate in team meetings and contribute to project planning
• Collaborate with team members to fulfill project objectives

Voluntary Recruitment

Automation Tester, Playwright

Artificial Intelligence

• Manage stakeholders to build trust and establish a strong foundation for long-term partnerships.
• Shape clients’ data strategy and target operating model.
• Lead and deliver transformative, innovative client engagements on time and within budget.
• Advise clients on data-driven insights and solutions.
• Conduct client-specific data value assessments.

Senior AI-Ready Data Advisor

• Lead discovery and solution design for GenAI use cases, translating business problems into concrete architectures (LLM decision, RAGs, fine‑tuning, agents, guardrails)
• Build end‑to‑end GenAI applications: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed.
• Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness.
• Perform model selection, prompting strategies, and fine‑tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including evaluation and A/B testing.
• Implement safety, compliance, and governance controls (input/output filters, PII handling, audit logs, human‑in‑the‑loop review where required).
• Collaborate with data engineers, product owners, and full‑stack developers on scalable architectures, SLAs, and integration with existing enterprise systems
• Gather technical requirements and estimate planned work.
• Mentor other data scientists/engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries, templates, and reusable components.
• Stay current with GenAI landscape (new open and hosted models, agentic frameworks, evaluation techniques) and perform targeted PoCs to validate them.

Senior Full Stack Data Scientist

Manager

• Oversee end-to-end incident management operations across the organization.
• Act as the primary liaison with project leads to drive timely resolution of major incidents, ensuring compliance with SLA and OLA commitments.
• Coordinate cross-functional technical teams to rapidly identify, troubleshoot, and resolve incidents.
• Ensure all incidents are properly logged, categorized, prioritized, and tracked within the ITSM tool.
• Continuously monitor incident progress and escalate when necessary to restore services as quickly as possible.
• Define, standardize, and continuously improve Incident Management processes, including the development of dashboards for end-to-end ticket visibility.
• Prepare and deliver incident reports, trend analysis, and operational insights within the defined scope.
• Serve as the central incident coordinator, actively driving resolution efforts during major incidents.
• Provide timely, accurate, and consistent communications to internal teams, leadership, and customers.
• Lead incident bridge calls, war rooms, and crisis management meetings.
• Deliver regular incident updates, executive summaries, and post-resolution briefings.
• Facilitate and coordinate with Service Level Management (SLM) on Root Cause Analysis (RCA), ensuring outcomes are actionable and measurable.
• Track and follow up on corrective and preventive actions to prevent incident recurrence.
• Maintain comprehensive lessons learned documentation and drive continuous improvement initiatives.
• Partner with SLM to analyze incident trends and performance metrics to identify areas for optimization.
• Recommend enhancements to processes, workflows, monitoring tools, and support practices.
• Collaborate closely with Problem Management and Change Management teams to ensure holistic service improvement.
• Ensure full compliance with ITIL best practices and organizational policies.
• Maintain and enhance Incident Management documentation, standards, and procedures.
• Conduct periodic audits and reviews to ensure process adherence and quality standards.

Incident Manager

Business Intelligence Developer

• Design, develop, and maintain interactive and visually appealing front-end solutions for business intelligence
• Work closely with business stakeholders to understand requirements
• Assist in gathering requirements for data analysis and reporting
• Translate business requirements into technical specifications
• Identify trends, patterns, and insights from data to support data-driven decisions

Front-end BI Developer

Solutions Engineer

• Develop and design solutions for technology architecture
• Collaborate with cross-functional teams to ensure successful implementation
• Analyze and improve existing systems and architecture
• Participate in technical discussions and decision-making

Solution Architect

• Depending on Your experience level acting as Senior Data Scientist or Consultant in Delivery of AI / GenAI projects – advising on the architecture, best practices, concepts, developing solution, leading technical team, etc. Making sure customer’s goals are met with technical vitality.
• Researching and preparing solutions for common DS/AI projects problems, defining the guidelines for others team.
• Being up-to-date with DS and AI market trends.
• Cooperate with Lingaro sales and delivery teams to identify and win new opportunities.
• Offers and presentations preparation.
• Developing DS&AI business through early-stage involvement into DS&AI customer journey.
• DS&AI value proposition and offering creation. Promoting it within the company and outside.
• Evangelization of the whole Lingaro and its customers in the field of AI/ML.
• Monitoring of trends, competitors, market opportunities and preparing thought leadership content.
• Helping team members and other units to achieve high customer satisfaction.
• Building and maintaining relations with customers (mostly through close cooperation during project acquisition, delivery and maintenance).

Senior AI Advisor

Chief Technology Officer

• Actively lead and contribute to high-impact data/AI projects that directly improve operations support outcomes — e.g., real-time incident enrichment, predictive alerting, automated root-cause analysis, change risk scoring, ticket clustering & autotriage, knowledge mining for support agents, and intelligent runbooks.
• Design and deliver scalable features embedded into operations support workflows and platforms (ServiceNow, Jira Service Management, monitoring tools, ITSM systems, etc.) in collaboration with multidisciplinary competency teams.
• Ensure solutions meet strict operations support SLAs for reliability, low latency, auditability, explainability, and zero-downtime deployment.
• Lead the architecture, development, and continuous enhancement of internal AIOps platforms and reusable components that power operations support teams — including integration with ITSM, observability (Prometheus/Grafana/ELK/Dynatrace/Splunk), ticketing, and automation tooling.
• Support MLOps/AlOps best practices specifically for production operations support Al systems: model monitoring in live ops environments, drift & performance degradation detection, rollback mechanisms, and cost control at operational scale.
• Serve as the lead Al technical authority and trusted advisor for all operations support programs, automation movements, and Al transformation efforts across service operations, NOC, support desks, infrastructure operations, and reliability engineering.
• Lead technical discussions, architecture reviews, PoCs, vendor evaluations, and solution selection whenever Al is being considered or applied to operations support challenges.
• Identify, prioritize, and drive the highest-ROI Al use cases in operations support — e.g., reducing MTTR/MTTD, automating Level 1 triage, predicting PI incidents, autogenerating post-mortems, optimizing shift handovers, and enabling proactive operations support.
• Build, mentor, and lead a high-performing squad of AIOps specialists focused on operations support outcomes.
• Foster a culture of rapid experimentation, production-first mindset, and relentless focus on operational impact (reduced toil, faster resolution, higher availability).
• Partner intensively with operations support leaders, incident managers, service owners, reliability engineers, ITSM/process teams, and infrastructure groups to align Al initiatives with operational priorities and pain points.

AI Operations Tech Leader

Backend Engineer

• Designing, developing, and maintaining the server-side logic of web applications. Implementing scalable and efficient server-side components and APIs.
• Working with relational and/or NoSQL databases to store and retrieve data efficiently. Designing and optimizing database schemas for performance and scalability.
• Integrating third-party APIs and web services to enhance application functionality. Developing custom APIs to facilitate communication between front-end and back-end systems.
• Implementing security best practices to protect against common web application vulnerabilities. Conducting regular security audits and implement necessary measures.
• Optimizing server-side code for maximum speed and scalability. Monitoring and troubleshooting performance issues.
• Collaborating with front-end developers, UI/UX designers, and other team members to ensure seamless integration of components.
• Using version control systems (e.g., Git) to manage and track changes to the codebase.
• Conducting thorough testing of server-side components to identify and fix bugs.
• Collaborating with QA engineers for comprehensive testing.
• Clear and comprehensive documentation for back-end systems and APIs.