Junior AI/ML Engineer (GenAI, AWS)

Role overview A global AI consultancy operating at the frontier of applied generative AI is hiring a junior engineer to join a senior delivery pod. The team partners with large enterprises in financial services, insurance, healthcare, and life sciences to deploy production-grade AI systems — including RAG pipelines and agentic applications — on AWS. The role offers hands-on contribution to real client work while building toward independent ownership of components and technical decisions.

Responsibilities - Build and contribute to RAG system components under senior guidance, gradually taking on more autonomy. - Write production code across the AI layer, backend services, and data pipelines, supported by code review. - Develop tests and help build evaluation harnesses for non-deterministic AI features, including investigating failure modes. - Help integrate AI components into backend services and RESTful APIs. - Support deployments of containerized systems to AWS through CI/CD pipelines. - Contribute to documentation, runbooks, and client handover materials, and participate in architectural discussions.

Requirements - 2+ years of software or ML engineering experience, with hands-on exposure to RAG systems in a production or near-production setting. - Solid fundamentals in Python and/or TypeScript, with the ability to ramp up in unfamiliar codebases. - Practical AWS experience (Lambda, S3, ECS, or similar) and exposure to containers and CI/CD in real projects. - Some experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and awareness of cost and latency trade-offs. - Basic working knowledge of model or agent monitoring, and exposure to evaluating non-deterministic systems. - Proactive, self-directed mindset; strong communication and problem-solving skills; B2+ English; comfortable working across distributed, multicultural teams.

Nice to have - Familiarity with the Claude ecosystem (Claude Code, CLAUDE.md, hooks, skills files) or strong ability to ramp up quickly. - Experience with Bedrock and Bedrock AgentCore, MCP server authoring, or agent-to-agent interoperability concepts. - Background in consulting, professional services, or embedded customer-facing delivery roles. - Exposure to Apache Spark, Apache Airflow, Kafka, or additional languages such as Go or Rust. - Pursuing or holding AWS or Claude Code certifications.

Benefits and work setup - Remote-friendly culture with distributed teams across North America, LATAM, and EMEA. - Long-term B2B collaboration with internal training programs and full support for Claude, AWS, and other professional certifications, plus conference attendance. - Private medical insurance or a dedicated medical budget, paid sick leave, vacation, and public holidays. - Equipment and tech provided, plus access to the latest AI tools and premium subscriptions. - Forward-deployed model working in small, senior teams with a clear focus on engineer development and career growth.