Senior Forward Deployed AI Engineer (GenAI, AWS)

United StatesRemoteFull-timesenior

Machine Learning EngineerData

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Quick Summary

Key Responsibilities

Understand customer operations firsthand: Spend the initial two to four weeks of an engagement performing the operator's role, learning the workflows, constraints,

Technical Tools

Machine Learning EngineerData

This role is designed for a senior, hands-on engineer who wants to combine advanced AI engineering with direct ownership of business outcomes. You will work alongside enterprise customers to understand their operations from the inside, redesign critical workflows, and build production-ready generative AI systems that deliver measurable impact. Rather than relying on traditional requirements gathering, you will immerse yourself in real business functions before determining what to automate and how. You will develop agentic applications, LLM-powered workflows, and evaluation frameworks across financial services, insurance, healthcare, and related industries. Working in small, senior teams, you will collaborate with business leaders, operators, and technical stakeholders to drive adoption and continuous improvement. This remote-friendly opportunity offers the autonomy to shape solutions from first principles while remaining deeply involved in the code.

You will take ownership of the full journey from understanding a customer's operational challenges to building, deploying, and improving AI-powered solutions. Your responsibilities will include:

Responsibilities

~1 min read

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Previous experience as a founder, CTO, or engineering leader who has chosen to return to hands-on individual contribution.
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Deep expertise in financial services, insurance, healthcare, or asset management.
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Experience in consulting, professional services, or embedded customer-facing engineering roles.
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Knowledge of data platforms, including data lakes, warehouses, streaming and real-time analytics, data mesh, data contracts, governance, and data quality.
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Experience with MLOps and traditional machine learning tools such as PyTorch, SageMaker, or MLflow.
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Expertise in model fine-tuning, distillation, inference optimization, or model serving.
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Experience with graph databases such as Neo4j or Amazon Neptune.
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Advanced infrastructure-as-code skills using AWS CDK, CloudFormation, or Terraform.
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Open-source contributions or public writing focused on applied AI.

What We Offer

~2 min read

✓Base salary of up to $200,000 per year.

✓On-target earnings (OTE) of up to $250,000, including applicable variable compensation.

✓Unlimited paid time off (PTO) policy.

✓401(k) profit-sharing plan available after a three-month probationary period.

✓Opportunity to work on advanced AI delivery initiatives involving Cowork Activation, Agentic SDLC, and industry-specific AI blueprint activations in financial services and healthcare.

✓The opportunity to influence how leading enterprises adopt AI, from strategic planning through initial production deployment.

✓Collaboration within small, senior delivery teams alongside Principal Architects and Forward Deployed Engineers.

✓The opportunity to help develop AI delivery tools, frameworks, and reusable engineering practices.

✓Remote-friendly working culture.

Location & Eligibility

Where is the job

United States

Remote within one country

Who can apply

About this job

Pay per year: $200,000 a year; 5% below the $210,000 median for Machine Learning Engineer jobs on Jobera (862 salaries).
Who can apply: United States
Posted: Today
Employer: has 5,412 open jobs on Jobera in 42 countries.