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Senior AI/ML Engineer (GenAI, AWS)

4 weeks, 1 day ago
North Macedonia, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Moldova, Montenegro
Full-time
Senior
Machine Learning Engineer
Software Development
Apache Airflow Apache Spark AWS Azure CI/CD GCP GitHub Actions GitLab CI Kafka Kubernetes Microservices NLP 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 37

Description

  • Work in a small pod alongside a Forward Deployed Engineer and a Forward Deployed Executive.
  • Build and ship production GenAI systems in customer environments, including cloud-native, LLM-based, and agentic AI solutions.
  • Design and optimize production RAG systems.
  • Build 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 to production on AWS or customer-required cloud platforms with containerized CI/CD delivery.
  • Implement LLMOps and AgentOps practices, including tracing, prompt/version management, monitoring, regression testing, and drift detection.
  • Participate in technical discussions and architectural decisions.
  • Conduct model evaluation, improve failure modes, and optimize performance, efficiency, and reliability.
  • Mentor junior and mid-level AI engineers and share knowledge through reviews, documentation, presentations, and workshops.

Requirements

  • 5+ years of experience in software engineering or ML engineering with production systems you were accountable for.
  • Strong AI/ML fundamentals and understanding of 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, and agent frameworks.
  • Experience building and optimizing production RAG systems.
  • Strong engineering fundamentals with a full-stack mindset across AI, backend development, and cloud infrastructure.
  • Proficiency in Python and/or TypeScript; depth matters more than stack.
  • Hands-on production AWS experience with Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar; GCP or Azure is a plus.
  • Experience with cloud-native delivery, including containers, ECS or Kubernetes, IaC, and CI/CD for AI pipelines.
  • Experience building or owning an evaluation suite for a non-deterministic system, including ground truth and release gating.
  • Experience with model and agent monitoring and drift detection.
  • Cost and latency discipline, including model tiering and caching.
  • Hands-on production experience with the Claude ecosystem, including Claude Code, CLAUDE.md, hooks, and skills files; spec-driven development is a strong plus.
  • Knowledge of MCP and why an agent may prefer it over a REST integration; authored server experience is a plus.
  • B2+ English and comfort collaborating across distributed, multicultural teams.
  • Proactive, self-directed mindset with comfort in ambiguity and ownership.
  • Excellent communication and problem-solving skills.
  • Experience in financial services, insurance, or healthcare is preferred.
  • Consulting, professional services, or embedded customer-facing delivery experience is preferred.
  • AWS and Claude Code certifications are preferred.
  • A2A / agent-to-agent interoperability knowledge is preferred.
  • CI/CD pipeline experience with GitHub Actions or GitLab CI is preferred.
  • Practical experience with NLP, LLMs, or recommendation engines is preferred.
  • Experience with Go, TypeScript, or Rust is preferred.
  • Experience with Apache Spark, Apache Airflow, or Kafka is preferred.

Benefits

  • Remote-friendly culture.
  • Internal training programs with support for Claude, AWS, and other professional certifications.
  • Conference attendance support.
  • 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 the tech needed for comfortable, productive work.

Interested in this position?

Apply directly on the company website

Apply Now

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