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Senior AI/ML Engineer (GenAI, AWS)

1 month, 2 weeks ago
Serbia, Slovakia, Slovenia, Spain, Poland, Ukraine, Armenia
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Airflow Apache Spark AWS Azure CI/CD GCP GitHub Actions GitLab CI Kafka Kubernetes LLM Microservices NLP Prometheus Python REST API TypeScript
Apply Now
Provectus

Provectus

Provectus provides consulting services in artificial intelligence and machine learning, assisting businesses in integrating AI solutions to meet their unique objectives and enhance their operational capabilities across various industries.

Professional Services
251-1K
Founded 2010
View All Jobs 33

Description

  • Work in a small pod with an FDE and an FDX to deliver client solutions.
  • Build and ship production GenAI systems in customer environments.
  • Build and optimize production RAG systems.
  • Create evaluation harnesses before feature development.
  • Write production code across AI, backend services, and data pipelines.
  • Integrate AI components into backend services and RESTful APIs.
  • Deploy systems on AWS or customer-required cloud platforms with containers and CI/CD.
  • Implement LLMOps and AgentOps practices including tracing, prompt/version management, monitoring, testing, and drift detection.
  • Contribute documentation, runbooks, enablement, and handover for client teams.
  • Participate in technical discussions, architectural decisions, model evaluation, and performance optimization.
  • Mentor junior and mid-level AI engineers through reviews, documentation, presentations, and workshops.

Requirements

  • 5+ years of experience in software or ML engineering with production systems ownership.
  • Proactive, self-directed mindset with comfort working through ambiguity and taking ownership.
  • Strong communication and problem-solving skills.
  • B2+ English and experience collaborating across distributed, multicultural teams.
  • Solid AI/ML foundations with the ability to reason about model failure modes.
  • Experience shipping production LLM applications and agentic workflows.
  • Experience with agentic orchestration, including multi-step workflows, graph-based orchestration, tool use, state management, and partial failure recovery.
  • Experience with LLM APIs such as Anthropic, AWS Bedrock, or OpenAI, plus agent frameworks.
  • Experience building and optimizing production RAG systems.
  • Strong engineering fundamentals across AI, backend development, and cloud infrastructure; Python and/or TypeScript proficiency.
  • Hands-on AWS production experience with services such as Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, and ECR; GCP or Azure is a plus.
  • Experience with containers, ECS or Kubernetes, IaC, and CI/CD for AI pipelines.
  • Experience owning an eval suite for a non-deterministic system and explaining measurement and release criteria.
  • Experience with monitoring, drift detection, cost discipline, caching, and model tiering.
  • Hands-on production experience with the Claude ecosystem, including Claude Code, CLAUDE.md, hooks, and skills files.
  • Spec-driven development experience is a strong plus.
  • MCP knowledge and the ability to explain its value over REST; authoring an MCP server is a plus.
  • Experience in financial services, insurance, or healthcare is a plus.
  • Consulting, professional services, or embedded customer-facing delivery experience is a plus.
  • AWS and Claude Code certifications are a plus.
  • A2A and agent-to-agent interoperability knowledge is a plus.
  • CI/CD experience with GitHub Actions or GitLab CI is a plus.
  • Experience with NLP, LLMs, or recommendation engines is a plus.
  • Additional language experience such as Go, TypeScript, or Rust is a plus.
  • Experience with Apache Spark, Apache Airflow, or Kafka is a plus.

Benefits

  • Remote-friendly culture.
  • Internal training programs with support for Claude, AWS, and other professional certifications.
  • Conference attendance support.
  • Career growth and active engineer development.
  • Access to the latest AI tools and premium subscriptions.
  • Long-term B2B collaboration.
  • Private medical insurance or a budget for medical needs.
  • Paid sick leave, vacation, and public holidays.
  • Equipment and all the tech needed for comfortable, productive work.

Interested in this position?

Apply directly on the company website

Apply Now

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