About the Position

We're seeking a Senior AI/ML Engineer with expertise in GenAI and AWS to join our team and develop production-ready AI solutions.

About Provectus

Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn 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.
Our team holds 100+ AWS certifications, is certified in the Anthropic Agentic SDLC program, and co-delivers AI Blueprint engagements.

You will work in a small, senior pod alongside an FDE and an FDX:

Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs.
Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution.
Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails. You'll have real ownership of components and of the technical decisions inside them.

Work in a pair with an FDE and an FDX.
Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions).
Build and optimize RAG systems for production use cases.
Build the evaluation harness before you build the feature.
Write production code across the stack - AI, backend services, data pipelines. We choose tools to fit the customer.
Integrate AI components into backend services and RESTful APIs.
Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection.
Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints.
Participate in technical discussions and architectural decisions.
Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability.
Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops.

Mindset

Proactive and self-directed; you push for clarity rather than waiting for a ticket.
Excellent communication and problem-solving skills.
Comfort with ambiguity and ownership.
B2+ English, comfortable collaborating across distributed, multicultural teams.

Experience in one of the industries: financial services, insurance, healthcare.
Consulting, professional services, or other embedded customer-facing delivery.
AWS and Claude Code Certifications.
A2A: you can explain agent-to-agent interoperability.
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, Kafka.

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.