Benefits:

• Freedom and ownership of meaningful work

• Personal development budget

• Meal allowance

• Sporting activities

• Free beers

Education Requirements:

• Degree in IT, Computer Science, Engineering, or a related field.

Experience Requirements:

• Experience as a Technical Implementation Manager, Solutions Engineer, or Technical Project Manager in AI, automation, or enterprise software

• Strong background in OOTB product implementation and configuration

• Knowledge of Javascript

• Experience with database management (SQL, Postgres, MongoDB)

• Experience with AI/ML platforms, API integrations, and technical project delivery

Other Requirements:

• Excel at breaking down complex problems and delivering clean, effective solutions.

• Data driven mindset, skill in making quick, well-founded decisions by considering various options and selecting the best solution.

• Capacity to generate new and effective solutions to challenging problems by thinking "outside the box" and applying creative approaches.

• Proficiency in project management methodologies and delivery frameworks

• Understanding of technical standards, architecture, and compliance requirements

Responsibilities:

• Implement AI solutions using OOTB products and standard approaches

• Execute technical project phases according to defined timelines and budgets

• Manage scope adherence and prevent scope creep through technical controls

• Own technical implementation from handoff through go-live

• Implement and maintain technical standards across all deliveries

Benefits:

• Mentorship from our legal expert

• Top market compensation package including company shares

• Personal development budget

• Meal allowance

• Free beers

Experience Requirements:

• Deep hands-on expertise with LLMs, AI agents, RAG, embeddings, and orchestration frameworks (LangChain, LangGraph, CrewAI, MCP, etc.)

• Strong track record in AI productization (building features beyond prototypes)

• Experience with enterprise automation domains (finance, GBS, ERP systems like SAP/Oracle/Workday, etc.) is a plus

• Proven ability to work cross-functionally with Product, Engineering, and Delivery teams

• Leadership qualities: able to coach, mentor, and inspire a growing AI team

Other Requirements:

• Pragmatic builder: combines research curiosity with execution discipline

• Be at the forefront of AI-native enterprise automation

• Work with leading global clients and partners

• Shape the future of our AI organization and products

• Join a collaborative, ambitious, and international team

Responsibilities:

• Lead applied AI research in LLMs, agent frameworks, RAG, embeddings, and multimodal document understanding.

• Drive productization: transform prototypes into scalable, reliable SaaS and on-prem solutions.

• Design and refine AI pipelines for automation (prompting, orchestration, validation, continuous learning).

• Collaborate with Product, PS, and CS teams to ensure customer requirements translate into robust AI features.

• Mentor and grow AI engineers, delivery specialists, and researchers; help define team structure.

Benefits:

• Freedom and ownership of meaningful work

• Personal development budget

• Meal allowance

• Sporting activities

• Free beers

Education Requirements:

• Education in the field of IT, Computer Science, Engineering or similar

Experience Requirements:

• Experience as a Technical Support Engineer, DevOps Engineer, or SRE in enterprise software or SaaS environments

• Strong background in system monitoring, troubleshooting, and incident management

• Experience with AI/ML systems, APIs, and integration platforms is a strong plus

• Proficiency in monitoring tools (Prometheus, Grafana, ELK stack, or similar)

• Understanding of cloud platforms (AWS, Azure, GCP) and containerization

Other Requirements:

• Customer service mindset with ability to communicate technical issues clearly

• Collaborative approach, working effectively with delivery and product teams

• Strong problem-solving skills with ability to architect complex automated solutions

• Data driven mindset, skill in making quick, well-founded decisions by considering various options and selecting the best solution.

• Understanding of technical standards, architecture, and compliance requirement

Responsibilities:

• Respond to technical incidents with defined SLA compliance

• Diagnose and resolve complex technical issues across the AI stack

• Escalate critical issues to appropriate technical teams when needed

• Monitor AI solution performance across all customer environments

• Implement proactive monitoring systems and alerting mechanisms