Junior AI/ML Engineer (GenAI, AWS)

Provectus; España; Remote; EUR 70,000 - 120,000; Full time

Benefits offered by this job

Remote-friendly culture

Internal training and certifications

Medical insurance or budget for health

Paid sick leave, vacation, and publicH

Job summary

Provectus seeks a senior AI/ML engineer to build and scale RAG system components, contribute to production code, and help integrate AI into backend services and APIs. You will collaborate with a small, senior pod across LATAM, Europe, and North America, with a focus on delivering real value to clients and expanding ownership over time.

The role offers exposure to Claude, AWS Bedrock, and other leading AI tools, with a remote-friendly culture and ongoing internal training.

Qualifications

• Proven experience in building or contributing to RAG systems in production or near-production environments.
• Strong Python and/or TypeScript skills; able to navigate unfamiliar codebases with ramp-up support.
• Hands-on AWS experience (Lambda, S3, ECS); readiness to grow into Bedrock and Bedrock AgentCore.
• Experience with containers and CI/CD in real projects.
• Familiarity with evaluating non-deterministic systems and basic model monitoring concepts.
• 2+ years of software or ML engineering experience, production exposure.

Responsibilities

• Build and contribute to RAG system components under senior guidance with growing autonomy.
• Write tests and help develop evaluation harnesses for features.
• Develop production code across AI, backend services, and data pipelines with code review support.
• Integrate AI components into backend services and RESTful APIs.
• Support deployment of systems to AWS (containerized, CI/CD) and grow independence.
• Contribute to documentation, runbooks, and client handover materials.
• Engage in technical discussions and architectural decisions, scaling ownership over time.
• Assist model evaluation efforts and investigate failure modes.

Skills

Python

TypeScript

RAG systems

AWS

CI/CD

LLM APIs

Production systems

Code review

Communication

Problem solving

Tools

AWS Bedrock

Claude Code

OpenAI API

GitHub Actions

GitLab CI

Job description

• Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.

• Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.

• Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.

  Where this role sits

  You will work in a senior pod alongside an FDE, an FDX, and Senior AI Engineers — contributing to real delivery work while building toward independent ownership.

Requirements:

Mindset

• Proactive and self-directed; you push for clarity rather than waiting for a ticket.

• Excellent communication and problem-solving skills.

• Comfortable with some ambiguity, with support from senior team members as you take on more.

• B2+ English, comfortable collaborating across distributed, multicultural teams.

Technical depth

• Hands-on experience building or contributing to RAG systems, ideally in a production or near-production setting.

• Solid engineering fundamentals; Python and/or TypeScript proficiency. Productive in an unfamiliar codebase with some ramp-up support.

• Practical AWS experience (Lambda, S3, ECS, or similar); ready to grow into Bedrock and Bedrock AgentCore.

• Some experience with containers and CI/CD in real projects.

• Exposure to evaluating non-deterministic systems — you've contributed to or run test/eval cycles, even if you haven't owned a full eval suite end-to-end.

• Basic working knowledge of model/agent monitoring concepts.

• Awareness of cost and latency trade-offs when working with LLMs.

• Some hands-on exposure to the Claude ecosystem (Claude Code, CLAUDE.md, hooks, skills files) is a plus, or strong ability to ramp up quickly.

• Practical experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) in real projects.

• 2+ years of software or ML engineering experience, including some exposure to production systems.

• Solid AI/ML foundations — you understand what the models do well enough to reason about common failure modes.

Nice to Have:

• Experience in one of the industries: financial services, insurance, healthcare.

• Consulting, professional services, or other embedded customer-facing delivery.

• AWS and Claude Code Certifications (or actively pursuing them).

• A2A: Interest in agent-to-agent interoperability concepts.

• CI/CD pipeline experience (GitHub Actions, GitLab CI).

• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.

• Experience in an additional language (Go, TypeScript, or Rust).

• Experience with Apache Spark, Apache Airflow, Kafkа.

• Experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build.

• MCP: you can say why an agent would prefer it to a REST integration, having authored a server is an additional plus.

Responsibilities:

• Build and contribute to RAG system components under senior guidance, with growing autonomy.

• Write tests and help build out evaluation harnesses for the features you work on.

• Write production code across the stack (AI, backend services, data pipelines) with code review support.

• Help integrate AI components into backend services and RESTful APIs.

• Support deployment of systems to AWS (containerized, CI/CD), taking on more of this independently over time.

• Contribute to documentation, runbooks, and client handover materials.

• Participate in technical discussions and architectural decisions, with an eye toward taking on more of this independently.

• Support model evaluation efforts and help investigate and improve failure modes.

• Take on increasing ownership of components and technical decisions as you grow in the role.

What We Offer:

• The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment

• A forward-deployed model working in small, senior teams alongside FDE and FDX

• A growing AI delivery practice where you help build the tooling and frameworks, not just use them

• Remote-friendly culture

• Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance

• Career growth; we actively develop our engineers

• Access to the latest AI tools and premium subscriptions

• Long-term B2B collaboration

• Private medical insurance or a budget for your medical needs

• Paid sick leave, vacation, and public holidays

• Equipment and all the tech you need for comfortable, productive work

How we hire:

1. Intro conversation. The role, your background and aspirations, tech questions.

2. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant

3. HR Interview. Soft skills and expectations

4. HM interview. Tech questions; a live engineering session is also possible