Artificial Intelligence

• You will own, build, and run your startup in fields such as AI.
• You will embark on an extensive personal development journey crafted by unicorn founders and follow a fully customized programme enhancing your goal, time, and energy management.
• You will receive support in hiring through our network to over 50,000 professionals and advice as well as best practices from serial entrepreneurs.
• You will receive intensive coaching to make your startup ready to raise millions in funding.
• You will iterate your product with us until having reached product-market-fit and receive support in building up a sales force or creating a marketing engine respectively.

AI Co-Founder / CEO

• Own enterprise-level business outcomes for agent-based automation, including efficiency, capacity, quality, client experience, and risk reduction.
• Define and communicate the long-term vision and strategy for agentic AI across global operations.
• Set strategic priorities across Fund Accounting, Middle Office, Transfer Agency, and Custody based on materiality, risk, and value.
• Sponsor identification and sequencing of high-impact automation opportunities across the operating model.
• Ensure alignment of product strategy with regulatory expectations, enterprise AI risk frameworks, and control standards.
• Govern translation of simplification objectives into coherent product portfolios, roadmaps, and investment cases.
• Provide executive oversight of agile delivery, ensuring consistency of standards, outcomes, and operational readiness across PODs.
• Own the full lifecycle governance of agentic AI solutions, including approval frameworks, human-in-the-loop models, escalation design, and decommissioning decisions.
• Establish enterprise standards for controls, auditability, explainability, and evidence capture in agent-based solutions.
• Set materiality thresholds, risk tolerances, and escalation models for autonomous and semi-autonomous execution.
• Make portfolio-level decisions to scale, pause, remediate, or retire agents based on performance, risk, and value realization.
• Oversee production performance management including accuracy trends, systemic failure patterns, and control effectiveness.
• Lead and develop senior Product Owners and product leaders, setting clear expectations and accountability for outcomes.
• Partner with senior operations, risk, compliance, audit, data, and technology leaders to ensure enterprise alignment.
• Define, track, and report value realization, risk metrics, and control outcomes to executive governance forums.
• Represent Global Delivery Simplification in senior leadership discussions related to AI strategy, operational resilience, and regulatory engagement.

Managing Director, Global Delivery Simplification

• Lead business development efforts to identify and pursue new opportunities in the AI and Machine Learning space
• Develop and execute go-to-market strategies for AI solutions, collaborating with marketing and sales teams to drive awareness and adoption
• Engage with partners and client executives to understand their needs and position our AI offerings effectively
• Respond to RFPs and prepare compelling proposals that highlight our AI capabilities and value proposition
• Act as a trusted advisor to clients, leveraging technical knowledge to provide insights and recommendations on AI solutions
• Collaborate with technical teams to ensure alignment between business objectives and AI solution development

Senior Manager – Artificial Intelligence

• Lead AI enablement across the group
• Conduct assessments: run structured assessments with each business team to map workflows, skills, and current AI usage before any enablement is planned.
• Find and solve pain points: collect the team's real pain points and use cases, prioritize them, and turn them into concrete enablement plans, working AI skills, or recommendations for specialist tools.
• Deliver concrete outcomes: ensure every workshop targets the team's own use cases and produces walk-away artifacts: working skills, prompts, and tools the team uses the next day.
• Activate champions: identify champions inside each team, work with them 1:1, and make their results visible to client leadership so momentum is seen at the top.
• Assess and track adoption KPIs: set realistic adoption targets per team, measure actual usage after each enablement cycle, and report progress transparently to the client and internally.

AI Education – Engagement Manager

• Process Automation & AI Implementation: Identifying, designing, and implementing automation opportunities using AI tools, machine learning, and robotic process automation (RPA) to streamline workflows. Spot bottlenecks in processes and implement pragmatic solutions.
• AI Tool Optimization: Proactively monitor the automation and AI landscape, produce structured assessments for new tools, and lead stakeholder alignment for the adoption or deprecation of tooling, owning the outcome of these decisions. Monitoring, maintaining, and improving the existing AI toolchain to ensure data governance and continuous performance improvements.
• Risk Management: Using AI for proactive, predictive maintenance and risk assessment to prevent operational failures, with main focus in Finance, Human Resources and Operations.
• Performance Tracking (ROI): Defining and monitoring key metrics (e.g., efficiency gains, reduction in manual effort) to measure the success of automated solutions.
• Information‑security projects and audits: implement technical solutions that enhance our security posture, and support ISO 27001/SOC 2 or other audits.
• Data integrity, backups, and availability: Schedule and monitor system exports, snapshots, and core‑IT backups; maintain retention policies to guarantee data completeness and recoverability.
• User support, training, and documentation: troubleshoot finance‑system issues, maintain runbooks, and deliver regular training sessions to all Operations teams and other stakeholders on system usage and security best practices.
• Collaborate and Coach the HRIS Manager who owns the HR systems/tech stack in identifying and implementing automation opportunities and AI usage to improve efficiencies, while keeping the employee experience in mind.

AI Operations & Automation Manager

• Managing AI projects and ensuring timely delivery
• Monitoring fixed project scope and maintaining effective client communication
• Managing monthly settlements with clients and team members
• Building and maintaining a healthy team culture through coaching, facilitation, and protecting the team from distractions
• Overseeing project resource allocation
• Defining and measuring metrics to track team progress, goals, and areas for improvement
• Working effectively across multiple projects simultaneously, with exceptional context-switching skills
• Helping with recruitment, onboarding, and offboarding processes
• Handling contracts and clauses that form the basis of cooperation with clients

AI Solutions Delivery Manager

• support clients in delivering AI-native products
• automate business workflows
• turn AI opportunities into production-ready solutions
• deliver MVPs, prototypes and production-ready AI solutions
• accelerate product development through AI-native engineering practices
• support discovery, estimation and technical decision-making

AI Agentic Consultant

• Own the architecture of EIS's agentic platform: agent orchestration, MCP-native tool ecosystems, agent memory (short-term, long-term, semantic), planning, and tool/function calling patterns reusable across product domains.
• Enable and provide support for domain teams for vertical insurance agents and the horizontal capabilities (RAG, retrieval, instructional flows) they compose from.
• Define and enforce levels of autonomy — assistive, semi-autonomous, autonomous — with explicit human-in-the-loop checkpoints, escalation paths, and reversibility for high-stakes actions in regulated workflows.
• Drive the MCP strategy: which capabilities EIS exposes as MCP servers to internal and partner agents, how our agents consume external MCP tools, and the tool registry, schemas, and versioning that keep this scalable.
• Maintain the multiple stack approach as a first-class capability: Typescript, and Java. Help teams to pick the right stack per agent and keep all aligned through shared configuration artefacts, prompt management, and evaluation tooling.
• Lead Architecture Decision Records (ADRs) for agentic capabilities; partner with Platform, Security/InfoSec, and DevOps so agents are observable, testable, sandboxed, and compliant by default.
• Drive AI DevOps for agents: trace capture and replay, eval harnesses (task success, tool-use correctness, regression), prompt and model versioning, cost and latency budgets per agent, and progressive rollout strategies.
• Set safe-AI standards for agentic systems: prompt injection and tool-poisoning defenses, action allow-lists, blast-radius controls, PII handling, data residency, and bias mitigation. Treat agent safety as a first-class architectural concern.
• Translate insurance use cases into production agent designs with product strategists and domain architects; provide technical leadership and mentorship; communicate agentic trade-offs (autonomy, reliability, cost, safety) clearly to executives, customers, and engineers.

Lead AI System Architect

• Own 1–2 series at a time (10–15 episodes per series, ~1 min per episode + a trailer)
• Work with our in-house AI copilot for character consistency, casting, and trailer generation.
• Direct, edit, and finish each episode yourself. You create scripts; you bring the storytelling and craft.
• We will teach you AI Content creation. If you have a strong background in film editing, you will learn fast.
• Collaborate with our team of AI Content Creators, tech team, other Short Film Directors, and our exec team

Senior AI Vertical Mini-Series Director – Freelance

• Own the end-to-end landing page production process, from strategy and planning to deployment and optimization.
• Develop high-converting comparison pages, advertorials, listicles, and product landing pages for paid acquisition campaigns.
• Define customer awareness levels, messaging angles, hooks, and conversion strategies for different audience segments.
• Use AI tools such as Manus, Claude, and proprietary systems to generate, refine, and scale landing page production.
• Collaborate closely with media buyers to align landing page strategy with campaign objectives and traffic sources.
• Create and test multiple landing page variants across different brands and product categories.
• Analyze landing page performance data and identify opportunities to improve conversion rates.
• Conduct competitor, customer, and market research to uncover winning messaging, objections, and emotional triggers.
• Develop and maintain swipe files, copy frameworks, and landing page best practices.
• Perform quality assurance reviews to ensure accuracy, persuasion, user experience, and mobile responsiveness.
• Build and document SOPs for landing page creation, optimization, and AI-assisted workflows.
• Stay current with direct-response marketing trends, conversion rate optimization techniques, and emerging AI tools.

Landing Page Expert – AI-Powered Direct Response

• Build internal tools and automation workflows for the operations team using Cursor and n8n
• Fix bugs and ship features in fast iterations - 3-4 production releases per day
• Design and deploy AI agents that automate repetitive operational tasks end-to-end
• Integrate with third-party APIs and internal systems without handholding
• Own QA - test your releases against real business logic before pushing
• Talk directly with ops users and translate vague feedback into precise solutions

AI Operations Engineer

• Set up and lead the newly established Ops AI Enablement team, including Senior AI Process Specialists and selected technical profiles.
• Define ways of working, roles, and collaboration model across Operations, CoE, Data, and technical enablement.
• Act as a people leader for the Ops AI Enablement team, fostering effective collaboration, clarity of ownership, and continuous learning.
• Play a key role in setting up the Ops AI Enablement team, including defining ways of working, interfaces to CoE, and collaboration with Operations leadership.
• Define and maintain the AI roadmap for Operations, aligned with Ops strategy, priorities, and maturity.
• Own the Ops AI innovation funnel and backlog, including intake, prioritisation, and sequencing of AI initiatives.
• Translate operational challenges into clearly scoped AI use cases with defined value hypotheses.
• Own the benefits tracking framework for Ops AI initiatives: define metrics, measurement methodology, and reporting cadence.
• Report AI value outcomes in regular business reviews, ensuring accountability for results across the Operations leadership team.
• Proactively flag initiatives that are underperforming and drive corrective action.
• Act as a critical link between complex technical AI possibilities and senior business leadership, providing clarity and actionable insights.
• Act as a key driver of AI adoption in Operations, ensuring AI solutions are embedded into day‑to‑day workflows.

Head of AI Operations

• Lead client discovery and pre-sales engagements, identifying AI opportunities, structuring business problems, defining AI project scopes, and shaping solution approaches.
• Own or significantly contribute to proposals, discovery workshops, business cases, solution concepts, and statements of work.
• Translate business objectives into data, AI, and GenAI strategies, ensuring that analytics, automation, and model development are directly linked to measurable business value.
• Advise senior stakeholders on technology and architecture choices, balancing feasibility, cost, risk, security, compliance, scalability, and expected business outcomes.
• Challenge assumptions and recommend the most appropriate AI approach for the client context, including when AI is not the right solution.
• Liaise between business, technical, delivery, and leadership teams to ensure clear communication and alignment across disciplines.
• Lead AI project delivery from a consulting perspective, overseeing execution quality, stakeholder alignment, business impact, and value realization.
• Co-create the strategy, vision, standards, and roadmap for Spyrosoft’s AI Consulting offering.
• Mentor consultants, engineers, and other team members in AI consulting practices, discovery methods, solution framing, and stakeholder communication.
• Communicate AI insights and recommendations clearly to executive, business, and technical audiences.

Lead AI Consultant

• Design and run short multi-turn conversations (typically 1–5 turns) intended to test AI personalization behavior
• Create prompts grounded in realistic personal scenarios to evaluate contextual understanding
• Review AI responses to determine whether personalization is correctly applied
• Check grounding quality to ensure the model does not invent unsupported claims about the user
• Evaluate integration quality — confirming personal signals are used naturally (not forced or robotic)
• Compare two responses side-by-side and determine which is more helpful, natural, and relevant
• Write clear, structured rationales explaining rankings and referencing specific conversation turns
• Verify debug information showing whether correct data sources were used
• Maintain strict workflow hygiene (including deleting evaluation conversations when required)

AI Evaluator, Polish

• Design and deliver a structured AI training strategy with Beginner, Intermediate, and Advanced learning pathways aligned to enterprise outcomes
• Create persona-based, workflow-driven learning journeys for executives, leaders, functional teams, and specialists
• Develop and maintain high-quality training assets (instructor-led and self-paced), including decks, labs, guides, videos, prompt packs, FAQs, and trainer kits
• Deliver global AI enablement through workshops, webinars, coaching, and hands-on, scenario-based sessions tied to real business workflows
• Teach practical AI and GenAI concepts, including prompt patterns, limitations, validation practices, and human-in-the-loop controls
• Lead Microsoft Copilot and M365 enablement, ensuring responsible, effective day-to-day usage aligned with security and privacy requirements
• Measure training effectiveness and adoption, continuously improving content and scaling impact through a global train-the-trainer and champion community model.

Senior Artificial Intelligence Trainer

• Build Creative Pipelines: Create and manage advanced, node-based generative AI workflows for production-ready visuals.
• Automate the Boring Stuff: Write simple scripts (Python or similar) to handle batch image processing and asset organization.
• Bridge the Gap: Act as the "translator" between our designers, technical engineering team and our Creative Technology Lead.
• Test & Ship: Find the best new AI models, test them, and turn them into reliable tools the whole design team can use daily.
• Define best practices, necessary documentation, and technical guardrails.

Artificial Intelligence jobs in Poland

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