Technical teams are overwhelmed by manual, repetitive tasks, fragmented tools, and rapidly growing data. These challenges increase errors, slow decision-making, and prevent teams from focusing on strategic initiatives.
What You'll Do:
Build and deploy clusters of AI agents that tackle multiple use cases across the IT domain.
Work hands-on with LLMs-installing, running, and fine-tuning models. We are not just calling APIs.
Build backend services for data ingestion, AI pipelines, and integrations.
Integrate open-source AI modules directly: read, tweak, and ship.
Operate in AWS (Lambdas, APIs, infrastructure) to power AI-driven features.
Collaborate directly with customers-strong English communication is essential.
What You'll Do:
Build and deploy clusters of AI agents that tackle multiple use cases across the IT domain.
Work hands-on with LLMs-installing, running, and fine-tuning models. We are not just calling APIs.
Build backend services for data ingestion, AI pipelines, and integrations.
Integrate open-source AI modules directly: read, tweak, and ship.
Operate in AWS (Lambdas, APIs, infrastructure) to power AI-driven features.
Collaborate directly with customers-strong English communication is essential.
Requirements:
5+ years of backend/software engineering experience with an AI-first and builder mindset and microservices architecture.
Practical experience building GenAI agents, beyond demos.
Strong Python skills (but this role is not just Python).
Familiarity with LLMs, prompting, and orchestration frameworks.
Startup mindset: shipped to production, owned systems end-to-end.
Comfortable reading docs, research papers, and experimenting independently.
Excited to adopt new development workflows and tools.
5+ years of backend/software engineering experience with an AI-first and builder mindset and microservices architecture.
Practical experience building GenAI agents, beyond demos.
Strong Python skills (but this role is not just Python).
Familiarity with LLMs, prompting, and orchestration frameworks.
Startup mindset: shipped to production, owned systems end-to-end.
Comfortable reading docs, research papers, and experimenting independently.
Excited to adopt new development workflows and tools.
This position is open to all candidates.
