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Forward Deployed AI Engineer (GenAI, AWS)

28 minutes ago
United States
Full-time
Lead
AI Engineer
Software Development
AWS AWS CDK Azure CI/CD CloudFormation Docker GCP Generative AI Kubernetes LLM Microservices MLflow Neo4j Python PyTorch Terraform TypeScript
Apply Now
Provectus

Provectus

Provectus provides consulting services in artificial intelligence and machine learning, assisting businesses in integrating AI solutions to meet their unique objectives and enhance their operational capabilities across various industries.

Professional Services
251-1K
Founded 2010
View All Jobs 38

Description

  • Spend the first weeks of an engagement doing the customer’s job to understand the workflow from the inside.
  • Work embedded inside client operations as part of the customer’s team rather than as a vendor.
  • Rebuild business functions and operating processes from first principles alongside operators and executives.
  • Build and ship production AI systems from the blueprint baseline into client-specific implementations.
  • Evaluate non-deterministic systems by building or owning evaluation suites and measuring outcomes.
  • Develop cloud-native solutions on AWS using containers, Kubernetes or ECS, IaC, and CI/CD.
  • Collaborate with senior stakeholders, including BU leaders and CTOs, on redesign and scoping conversations.
  • Own ambiguous engagements end to end and focus on business outcomes rather than hours or task lists.
  • Contribute lessons learned from client work back into Provectus industry blueprints and delivery frameworks.

Requirements

  • 8+ years of software development experience, with a substantial share in production code.
  • Hands-on engineering experience and intent to remain hands-on.
  • Willingness to spend weeks doing operational customer work before writing code.
  • Ability to learn unfamiliar business domains quickly and speak credibly with domain experts.
  • Experience shipping GenAI or LLM systems to production, beyond demos or notebooks.
  • Experience building or owning an evaluation suite for a non-deterministic system.
  • Strong engineering fundamentals and the ability to be productive in unfamiliar codebases or languages.
  • Proficiency in Python and/or TypeScript.
  • Cloud-native delivery experience on AWS; GCP or Azure is a plus.
  • Solid AI/ML foundations and understanding of model failure modes.
  • Fluent written and spoken English.
  • Preferred: prior experience as a founder, CTO, or engineering leader returning to individual contribution.
  • Preferred: deep experience in financial services, insurance, healthcare, or asset management.
  • Preferred: consulting, professional services, or other embedded customer-facing delivery experience.
  • Preferred: data platform experience with data lakes, warehouses, streaming, real-time analytics, data mesh, data contracts, governance, and data quality.
  • Preferred: MLOps and classical ML experience with PyTorch, SageMaker, or MLflow.
  • Preferred: experience with fine-tuning, distillation, or inference/serving optimization.
  • Preferred: graph database experience with Neo4j or AWS Neptune.
  • Preferred: IaC depth with AWS CDK, CloudFormation, or Terraform.
  • Preferred: open-source contributions or public writing on applied AI.

Benefits

  • Remote-friendly culture.
  • Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations.
  • Opportunity to shape how leading enterprises adopt AI from strategy through first deployment.
  • Small, senior teams working alongside Principal Architects and Forward Deployed Engineers.
  • The chance to help build the tooling and frameworks behind the AI delivery practice.
  • Work across financial services and healthcare clients on high-impact engagements.

Interested in this position?

Apply directly on the company website

Apply Now

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