Genios AI

Software Engineer – AI Platform

Genios AI

full-time

Posted on:

Location Type: Hybrid

Location: Santa Clara • California • United States

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Tech Stack

GoGRPCMicroservicesPythonPyTorchScikit-LearnTensorflow

About the role

  • Build and scale AI/ML and GenAI pipelines from experimental workflows to production-ready systems.
  • Integrate model training, evaluation, deployment, and monitoring into product workflows
  • Deploy and manage GenAI solutions such as chatbots, RAG applications, and predictive analytics tools.
  • Operationalize LLMs and AI agents, including prompt orchestration, chaining, and fine-tuning.
  • Benchmark models, develop evaluation frameworks, and improve reliability and auditability.
  • Implement observability, monitoring, and rollback mechanisms to ensure secure, scalable deployments.
  • Work across the stack—from backend systems to product SDKs—to deliver AI features directly into user-facing applications.
  • Prototype rapidly, gather feedback, and iterate while keeping scale and maintainability in mind.
  • Own critical product components and take responsibility for delivering robust, production-grade features.
  • Collaborate cross-functionally with data scientists, product managers, and engineers to scope specifications and solve real customer problems.
  • Debug complex issues and perform root cause analysis across model pipelines, infrastructure, and product layers to ensure reliability and continuous improvement.

Requirements

  • BS or MS in Computer Science, Statistics, or Mathematics, or equivalent experience.
  • Strong software engineering background with proven experience shipping production systems.
  • 3+ years of experience in ML/DL pipelines, deployment, and applied AI solutions.
  • Proficiency in Python or Go with frameworks like TensorFlow, PyTorch, Scikit-Learn, FastAPI, or gRPC.
  • Experience with LLM and AI frameworks such as Langchain, LlamaIndex, Hugging Face Transformers, and OpenAI API.
  • Knowledge of RAG architectures, embeddings, reranking models, and LLM-based dialogue systems.
  • Experience building and scaling backend platforms, APIs, and microservices.
  • Comfortable working full-stack, from model APIs down to user-facing integrations.
  • Have shipped AI features that users actually use; production experience over theoretical knowledge.
  • Track record of building reliable products with strong attention to detail and usability.
  • Autonomous and excited about taking ownership over major initiatives.
  • Frequent user of AI products (Cursor, Claude Code, Copilot, etc.) during the development lifecycle.
Benefits
  • Competitive Compensation
  • Unlimited PTO
  • AI Assistants for work (Coding, General Purpose, etc.)
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI/ML pipelinesGenAI solutionsmodel trainingmodel evaluationmodel deploymentPythonGoTensorFlowPyTorchScikit-Learn
Soft Skills
collaborationproblem-solvingattention to detailownershipautonomyiterationdebuggingroot cause analysiscommunicationfeedback gathering
Certifications
BS in Computer ScienceMS in Computer ScienceBS in StatisticsMS in StatisticsBS in MathematicsMS in Mathematics