Senior AI/ML Engineer

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, design and build a working AI solution, present to the client, and transfer 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. Responsible for evaluation, observability, and guardrails. Real ownership of components and technical decisions.

Qualifications

• Proactive and self-directed; 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; understand model performance and failure modes.
• Experience shipping production LLM applications and agentic workflows.
• 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 across AI, backend development, and cloud infrastructure.
• Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar.
• Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines.
• Experience with model and agent monitoring, drift detection.
• Cost and latency discipline: model tiering, caching, and workload cost estimation.
• Hands-on production experience with the Claude ecosystem.
• MCP: can explain agent-to-agent interoperability.

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.
• CI/CD pipeline experience (GitHub Actions, GitLab CI).
• Practical experience with use cases from 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.
• Build and optimize RAG systems for production use cases.
• Build the evaluation harness before building 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 required).
• Implement LLMOps and AgentOps practices.
• Contribute to enablement and handover: clear documentation, runbooks, and pairing with client engineers.
• Participate in technical discussions and architectural decisions.
• Conduct model evaluation and optimize model performance.
• Mentor junior and mid-level AI engineers, conduct code reviews, and share knowledge across the team.

Benefits

• Opportunity to shape how leading enterprises adopt AI.
• A forward-deployed model working in small, senior teams.
• A growing AI delivery practice where you help build tooling and frameworks.
• Remote-friendly culture.
• Internal training programs with support for certifications and conference attendance.
• Career growth; actively develop engineers.
• 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 tech for comfortable, productive work.