[Hiring] Senior AI/ML Engineer @Provectus

Role Description

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: Help turn business problems into agentic systems that run 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.

Qualifications

• 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.
• 5+ years in software or ML engineering, with production systems you were accountable for.
• Solid AI/ML foundations; you understand what the models do well enough to reason about failure modes.
• Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks.
• Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
• Experience building and optimizing RAG systems in production.
• Strong engineering fundamentals; full-stack mindset, comfortable across AI, backend development, and cloud infrastructure.
• Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus.
• Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines.
• Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files.
• MCP: you can say why an agent would prefer it to a REST integration.

Requirements

• 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.

Responsibilities

• 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.
• 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.
• 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.

Benefits

• 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.