Role Description The Principal AI Solutions Engineer is a hands-on individual contributor responsible for designing, building, and deploying production-ready AI solutions, with a strong focus on AI agents that reason, use tools, and complete end-to-end business tasks. The Principal AI Solutions Engineer sits within the AI / Digital Center of Excellence (CoE) and partners across the enterprise to convert real workflows, SOPs, and decision logic into secure, scalable AI-driven solutions. The Principal AI Solutions Engineer blends deep engineering execution with a consulting mindset. You will work directly with business leaders to frame problems, identify value, and deliver AI agents that measurably improve speed, cost, quality, or cycle time. Success is defined by solutions shipped, adopted, and delivering impact, not slideware. The Principal AI Solutions Engineer has no people management responsibilities and is strongly build-first. Key Responsibilities - Re-imagine enterprise work with an AI-first mindset: Diagnose end-to-end processes and identify high-value workflows suitable for AI-driven transformation. - Process-to-agent translation: Map workflows, SOPs, controls, and decision logic; facilitate working sessions with business SMEs to decompose them into agent-friendly steps (reasoning, execution, validation, escalation, human-in-the-loop). - Consultative problem framing & value prioritization: Partner with business leaders to structure ambiguous problems, quantify impact, and translate them into clear AI solution hypotheses. - Build AI agents (hands-on): Develop agents using Python and modern agent frameworks to analyze information, follow procedures, call tools/APIs, and complete tasks end-to-end. - Integrate with enterprise systems: Build logic layers and integrations across APIs, workflow tools, data platforms, and approved enterprise data sources. - Deploy securely to production: Use enterprise AI platforms (e.g., Azure AI Foundry) with appropriate security, access controls, monitoring, and reliability practices. - Production quality & Responsible AI: Implement guardrails, observability, evaluation, and fallback mechanisms to ensure safe and reliable operation. - Operate in Agile delivery cycles: Manage work through backlogs, iterative releases, and measurable outcomes in close collaboration with IT, data, security, and platform teams. Qualifications - Bachelor’s degree in business, Engineering, Computer Science, Information Systems, or a related field; advanced degree preferred. - 5+ years of experience in software engineering, automation, process engineering, or related technical roles delivering production solutions. - 1+ year hands-on experience building with LLM APIs and/or agent frameworks (not just experimentation, shipping is preferred). - Experience operating in consulting-style or advisory roles, including problem structuring, executive communication, and influencing without authority. - Proven ability to translate ambiguous workflows into scalable enterprise solutions. - Strong communication skills to translate between business needs and technical implementation. Preferred Experience - Experience deploying solutions using enterprise AI platforms and services (e.g., Azure Foundry AI capabilities and deployment patterns). - Familiarity with a “model garden” approach (using multiple LLM providers/models through a unified platform) and selecting the right model for task quality, latency, and cost. - Experience in regulated, complex, or global enterprise environments; comfort operating with security/compliance constraints. - Background in process transformation, operational excellence, or management consulting style problem solving, including hypothesis-driven analysis and executive-level communication. Requirements - All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. - For U.S. locations that require disclosure of compensation, the starting pay for this role is between $165,000.00 and $190,000.00. The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors. - U.S. based employees may be eligible for short-term and/or long-term incentives. They may also be eligible to participate in medical, dental, vision insurance, disability and life insurance, a 401(k) plan and company match, a tuition reimbursement program (select degrees), company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive sick time, floating holidays and paid vacation. Company Description Bausch + Lomb (NYSE/TSX: BLCO) is a leading global eye health company dedicated to protecting and enhancing the gift of sight for millions of people around the world—from the moment of birth through every phase of life. Our mission is simple, yet powerful: helping you see better, to live better. Our comprehensive portfolio of over 400 products is fully integrated and built to serve our customers across the full spectrum of their eye health needs throughout their lives. Our iconic brand is built on the deep trust and loyalty of our customers established over our 170-year history. We have a significant global research, development, manufacturing and commercial footprint of approximately 13,000 employees and a presence in approximately 100 countries, extending our reach to billions of potential customers across the globe. We have long been associated with many of the most significant advances in eye health, and we believe we are well positioned to continue leading the advancement of eye health in the future.

• Design and build the AI Agent Builder, a low-code tool for creating, testing, and deploying AI agents • Integrate LLM inference and agentic capabilities into gaiia's existing Workflow Engine • Build reusable AI components used by other squads across the platform • Evaluate and integrate new model capabilities, tool-use patterns, and orchestration frameworks • Contribute to architectural decisions around prompt design, evaluation, guardrails, and observability for production AI systems • Design, develop and deploy GraphQL APIs for both internal and external use • Develop intuitive interfaces for non-technical users to build and manage their own AI agents

Role Description Join PwC Slovakia as a Junior AI Engineer, where you'll have the opportunity to grow your skills and contribute to AI and data science solutions for leading global clients. This role is designed for developers and engineers who want to build, integrate, and deploy machine learning systems and data-driven applications. We are looking for candidates who enjoy coding in Python, working with data, and turning ideas into reliable, scalable solutions. - Projects you could be involved in: - Natural Language Data Exploration: Develop dashboards powered by AI for intuitive business data analysis. - Document Interaction: Design tools enabling seamless interaction with unstructured and structured text documents. - Knowledge Assistant: Implement ERP transformation with AI-powered tools to resolve employee inquiries efficiently. - Agricultural Monitoring: Utilize Computer Vision for analyzing satellite imagery on a large scale. - Automated Reconciliation: Create systems to identify anomalous transactions in accounting ledgers. - What You’ll Do: - Project Participation: Participate in AI and data science projects from conception to deployment, contributing to solution design and supporting timely delivery of assigned tasks. - Solution Development: Support the development of AI and ML solutions with a strong focus on Python-based implementation, working across areas such as Large Language Models (LLMs), RAG, classical machine learning and data analysis. - Learning & Development: Continuously develop technical skills by following AI and data science trends, learning new approaches, and contributing to improvements of existing solutions and processes. Qualifications - Solid programming skills in Python (e.g. pandas, numpy, scikit-learn, plotly). - Hands-on academic, project, or entry-level experience with machine learning, data science, NLP, Computer Vision, or Generative AI (LLMs, RAG). - Basic experience with SQL databases; familiarity with NoSQL databases is an advantage. - Strong analytical mindset with the ability to approach problems logically and creatively. - Ability to work independently on assigned tasks and deliver results with guidance when needed. - Fluent in English (B2 level or higher). Requirements - Ability to write and understand code is essential. - Experience with other programming languages is a plus. - Strong foundations in statistics and ML fundamentals are valued. Benefits - Work format: Remote or in a comfortable office in Lviv - you choose. - Development: Personal development plan, mentoring, English and Polish language courses. - Stability: Official employment from day one, annual review of salary and career prospects. - Corporate culture: Events that unite the team and a space where everyone can be themselves.

Role Description - Design and implement evaluation frameworks (evals) to assess LLM and agentic AI system quality, including accuracy, consistency, safety, and task completion rates. - Build and maintain automated test pipelines for AI features, covering unit, integration, and end-to-end scenarios across agentic workflows. - Develop tooling to detect regressions in model behavior, prompt outputs, and agent decision-making across releases. - Define and track quality metrics for AI systems (e.g., hallucination rates, tool-use accuracy, latency, failure recovery) and surface findings clearly to stakeholders. - Collaborate with engineers and product managers to identify edge cases, adversarial inputs, and failure modes specific to multi-step agentic pipelines. - Contribute to prompt evaluation strategies, including red-teaming, adversarial testing, and bias/fairness assessments. - Participate in design and code reviews with a quality-focused lens, raising concerns about testability and reliability early. - Help define and document quality standards and best practices for AI/ML features across the team. - Other duties as assigned. Qualifications - Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. - 3–5 years of professional software engineering or quality engineering experience. - Hands-on experience working with LLMs or agentic AI systems (e.g., GPT-4, Claude, Gemini, or open-source models). - Proficiency in Python for scripting, test automation, and data analysis. - Experience designing and running evaluations (evals) for generative AI or LLM-powered features. - Solid understanding of software testing principles: unit, integration, regression, and end-to-end testing. - Familiarity with agentic frameworks and concepts (e.g., tool use, multi-step reasoning, retrieval-augmented generation, memory). - Experience with CI/CD pipelines and integrating automated tests into development workflows. - Strong analytical skills — able to interpret probabilistic outputs and distinguish meaningful regressions from expected variance. - Strong written and verbal communication skills; ability to clearly document findings and present quality data to non-technical stakeholders. - Detail-oriented, with a structured approach to exploring edge cases and failure scenarios. - Ability to work in a fast-paced environment and manage multiple priorities effectively. Requirements - Experience with prompt engineering and systematic prompt evaluation methodologies. - Familiarity with AI safety, alignment, or responsible AI concepts (e.g., hallucination mitigation, bias detection, guardrails). - Exposure to agentic orchestration frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or similar). - Experience with vector databases or RAG pipelines (e.g., Pinecone, Weaviate, pgvector). - Knowledge of observability and monitoring tools for AI systems (e.g., LangSmith, Weights & Biases, Arize). - Background in data science or ML experimentation practices. - Experience with version control systems (Git) and defect-tracking tools (e.g., Jira). - Exposure to cloud platforms (e.g., AWS, Azure, GCP) in the context of deploying or testing AI services. Benefits - Medical, Dental & Vision Benefits - 401(k) Savings Plan with Company Match - Flexible Planned Paid Time Off - Generous Sick Leave - Inclusive & Welcoming Environment - Purpose-Driven Culture - Work-Life Balance - Commitment to Community Involvement - Employer-Paid Parental Leave - Employer-Paid Short-Term Disability - Remote Work Flexibility