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Recruitment Software
Post jobs, import profiles, add screening questions, and manage hiring all in one place with personalized questions and control the entire recruitment process.
Recruitment Service
Let our expert team handle the key stages of tech recruitment for you with our specialized team acting in the main stages of recruitment.
Talent Pool
Top-tier Brazilian tech professionals, pre-vetted and ready for action, all pre-selected and ready for new opportunities.
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Discover the perfect plan for your needs.
Use Cases
Build my own team
Define the profile, validate with our experts, and assemble your tech team with full control over every step.
Autopilot
Put tech recruitment on autopilot and receive pre-vetted candidates matched to your needs without lifting a finger.
Complete Solution
From sourcing to hiring — an end-to-end tech recruitment experience powered by AI, specialists, and a curated talent pool.
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Contents about people management, organizational culture and trends in human resources.
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EN
Factspan
Seattle, Washington
Remote
(Anywhere)
Salary Range
Not informed
Not informed
Experience Level
Senior
Requirements
Desired Skills
Tasks and Responsibilities
We are looking for a Senior Backend AI Engineer to architect, build, and scale production-grade backend systems that power AI and machine learning workflows. In this role, you will design microservices, integrate LLMs and Gen AI applications, and lead the technical execution of end-to-end AI platforms.
You will work closely with data scientists, frontend engineers, and platform teams to operationalize AI pipelines, maintain high standards of code quality, and ensure systems are secure, observable, and performant at scale.
Strong SQL, Python, and query analysis skills are required. Proficiency in Python, JavaScript (React/Angular) with experience building basic UI using React or similar frameworks, and Java or Go for backend development.
Microservices architecture, RESTful APIs, distributed systems. Experience building data pipelines, APIs, and microservices.
TensorFlow, PyTorch, LangChain, Vertex AI, LLMs, and general Gen AI/Agentic AI experience.
Experience designing and implementing production-grade Agentic AI systems using Google ADK, including multi-agent workflows, tool-calling, and Model Control Plane (MCP) Server services for exposing internal tools/APIs. Google ADK experience is highly preferred.
GCP, Kubernetes, Docker. GCP experience is highly preferred.
NoSQL databases such as MongoDB and Cosmos DB, SQL, and BigQuery experience are highly preferred.
Profiling, caching strategies, query optimization, and the ability to identify performance bottlenecks and optimize performance using Gen AI. Observability experience is expected.
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