Generative AI Operations Engineer (GenAI Ops)
New
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EPAMAI Operations
Opportunity to work remotely within PolandFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- En B2
- Experience
- 3+ years
- Required Skills
- AWSDockerPythonKubernetesCI/CDTerraformMLOpsGenerative AI
Requirements
- 3+ years in a DevOps, SRE, or MLOps role with a focus on cloud infrastructure (AWS, GCP, or Azure).
- Proficiency in building and managing CI/CD pipelines and at least one scripting language (Python or Bash).
- Familiarity with IaC tools (e.g., AWS CDK, CloudFormation, Terraform) and containerization/orchestration (Docker, Kubernetes).
- Proven track record of deploying and operating LLM inference (e.g., vLLM, Triton, TGI, Ray Serve, KServe/Seldon).
- Hands-on experience with LLM/app tracing and metrics (e.g., OpenTelemetry, Langfuse, Arize Phoenix, WhyLabs).
- Experience operating retrieval pipelines including embedding generation, indexing strategies, and vector databases (Pinecone, Weaviate, Milvus, FAISS).
- Experience running multi-agent workflows (LangGraph, CrewAI, AutoGen) including state management and auditing.
- Experience implementing security guardrails such as secrets isolation, prompt-injection defenses, and PII redaction.
- B2 proficiency in English.
Responsibilities
- Design, implement, and maintain robust, automated CI/CD pipelines for training, evaluating, and deploying LLMs and AI agents.
- Design, deploy, and manage sophisticated, multi-agent systems ensuring seamless Agent-to-Agent (A2A) communication.
- Implement and manage secure, scalable integrations between AI agents and external tools/APIs using standards like Model Context Protocol (MCP).
- Utilize IaC services or tools like Terraform to define and manage infrastructure for GenAI workloads.
- Implement comprehensive monitoring and logging solutions to track model and agent performance, resource utilization, and system health.
- Design and implement scalable architectures for model serving and inference to optimize performance and cost.
- Enforce security best practices, guardrails, and compliance standards for GenAI infrastructure and data.
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