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We are looking for an experienced Product Manager to join our product team and help drive the development of our platform. In this role, you will lead product initiatives end-to-end - from problem discovery and product definition to delivery and continuous improvement.
A significant part of the role involves working on integrations with external systems, defining API-based capabilities, and enabling seamless data exchange between us and third-party services.
You will work closely with engineering, design, data, and business stakeholders to build scalable product capabilities that solve real problems for accounting professionals and deliver measurable business impact.
This role requires strong product thinking, analytical capabilities, and the ability to translate complex business and technical requirements into clear, well-defined product solutions.
Key Responsibilities:
Own product initiatives from discovery through delivery and continuous improvement
Work closely with engineering teams to define product requirements, user stories, KPIs, and acceptance criteria
Define API-based capabilities and support integration flows between external systems, enabling seamless data exchange between us and third-party services
Collaborate with design to deliver clear, user-centered product solutions
Define product roadmaps aligned with company strategy
Analyze product usage, funnels, and customer feedback to drive data-informed decisions
Use data extensively to identify opportunities, validate hypotheses, and guide prioritization
Work cross-functionally with customer success, support, and business teams
Lead feature prioritization and backlog management based on impact and data
Contribute to the evolution of our platform and modular product capabilities
Utilize modern AI tools as part of daily product work, including research, analysis, documentation, ideation, and experimentation (including A/B testing and validation loops)

As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.

Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.


Key Job Responsibilities and Duties:

Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.

Dealing with massive textual sources to train GenAI foundation models.

Solving issues with data and data pipelines, prioritizing based on customer impact.

End-to-end ownership of data quality in our core datasets and data pipelines.

Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.

Providing tools that improve Data Quality company-wide, specifically for ML scientists.

Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.

Acting as an intermediary for problems, with both technical and non-technical audiences.

Promote and drive impactful and innovative engineering solutions.

Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

A leading fintech information provider, delivering digital solutions in labor law, taxation, finance and pensions.
We are looking for a Product Manager.
Key Responsibilities:
Implementation of the product's strategy and vision and make sure its aligned with the company's overall objectives and market trends in the legal industry.
Conduct in-depth market research and analysis to identify emerging trends, competitive landscape, product market fit, and customer needs within the legal technology space.
Define and prioritize the product roadmap based on strategic initiatives, customer feedback, and market opportunities, ensuring alignment with business goals and resources.
Lead cross-functional agile teams through the product development lifecycle, from ideation and requirements gathering to design, development, and launch, while maintaining focus on quality and timeliness.
Ensure that all product features and functionalities comply with relevant legal regulations, data privacy laws, and security standards.
Identify opportunities to embed AI capabilities into the product: automations, intelligent workflows, and decision-support features that add measurable value to customers.
Apply AI tools in day-to-day PM work: research, spec writing, discovery synthesis, backlog management, and stakeholder communication.

As a Machine Learning Engineer, you will work closely with experienced engineers and ML scientists to build scalable, production-grade GenAI applications. Your work will focus on designing, training, and deploying ML systems leveraging LLMs,, recommendation systems, and agent-based architectures, using state-of-the-art technologies. These solutions will directly power customer-facing experiences and play a key role in shaping the future of AI-driven travel products.

Key Job Responsibilities and Duties:

Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.

Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.

Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, chatbots, translation or other innovative applications.

Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.

Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.