A hands-on engineering role focused on building high-quality software and AI agents to solve business problems. Working directly with business teams like call center reps and attorneys to deliver measurable results using AWS.
Compensation
$120,000—$160,000 USD
Responsibilities
Embed with the business: Spend time with the teams doing the work to understand how it gets done and where it gets stuck
Pick the right problem: Agree with business owners on one measurable problem, take a baseline before building, and define how success will be measured
Lead by example: Design and implement reliable systems across the backend, frontend, and cloud infrastructure on AWS
Build with AI: Build AI agents and workflows for areas such as our call center and client intake across chat, text and voice, the early steps of litigation, practice areas beyond personal injury, and new AI products the firm is building
Embed directly inside a strategic enterprise customer to independently design, build, deploy, and run AI-powered production systems alongside the customer's engineering team.
Locations (5)
Boston, Massachusetts, United States
Seattle, Washington, United States
New York, New York, United States
East Palo Alto, California, United States
San Francisco, California, United States
Compensation
Forward Deployed Engineer (FDE), AWS Forward Deployed Engineering, US Government
Embed directly inside a strategic enterprise customer to independently design, build, deploy, and run AI-powered production systems alongside the customer's engineering team.
We are looking for a skilled senior engineer with hands-on experience with Copilot, Copilot Studio, and the creation of agents. This role advocates and advances modern, Agile solution delivery practices and evangelizes great design and engineering practices.
Compensation
Pay range: $55.06 - $63.06 per hour
Responsibilities
Define and prioritize product requirements, enabling developers to use Copilot & Prompt Engineering
Utilize hands-on experience with Copilot for instructions, prompts, skills, and agents
Apply hands-on experience in agentic development
Partner with Data Engineers, Data Scientists, UI/UX Designers, App Developers, product owners, and clients in the development of solutions
Coordinate with multiple stakeholders including Technology, Sales, Client Education, Finance, and Legal
Requirements
Bachelor's degree
equivalent
Nice to have: Ability to thrive in a fast-paced, team-based environment
Nice to have: Strong written and verbal communication skills
Nice to have: Strong focus on troubleshooting and issue resolution
Solution Architect responsible for designing and operating solutions in regulated global environments, focusing on Azure cloud-native solutions and AI-enabled features.
This is a remote Machine Learning Engineer III role within the HS Code Classification team, focusing on building intelligent systems, GenAI, and ML services for product classification.
Responsibilities
Build and improve ML systems for product classification, document understanding, data quality checks, and retrieval
Fine-tune, test, and deploy models, including transformers and small language models
Build AI agents that reason through multi-step tasks and use MCP to connect to tools and data
Write backend services, APIs, and pipelines that bring models into production
Set up evaluations to track accuracy, speed, reliability, and where models fail
Requirements
Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field.
Lead the AI roadmap and delivery of secure, scalable AI solutions that improve decision-making, streamline workflows and create measurable business value.
Compensation
$146,575.00 - $229,600.00
Responsibilities
Own the AI roadmap, prioritizing use cases with business leaders based on value, feasibility and risk.
Lead and develop AI engineers and analysts; establish clear delivery, quality and engineering standards.
Guide AI assistants, agentic workflows and decision-support solutions from discovery and pilot through deployment and continuous improvement.
Partner with data engineering, analytics, technology and risk teams to ensure trusted data, appropriate controls and clear human accountability.
Drive adoption and measure outcomes across business impact, user experience, productivity, reliability and cost.
USA, CA, East Palo Alto - 165,200.00 - 223,600.00 USD annually
USA, CA, San Francisco - 165,200.00 - 223,600.00 USD annually
USA, MA, Boston - 143,700.00 - 194,400.00 USD annually
USA, NY, New York - 158,100.00 - 213,800.00 USD annually
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually
Responsibilities
Embed within customer engineering teams and translate requirements into technical designs
Build production AI applications and integrate foundation models and data sources
Own production for your workstream across the full software lifecycle
Mentor and train new team members
Accelerate customer adoption and expand AI adoption within customer engagements
Requirements
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
Nice to have: customer production environments
Nice to have: AI/ML production
Nice to have: founder or engineering lead experience
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.
Responsibilities
Embed within customer engineering teams
Build production AI applications
Own production for your workstream
Mentor and uplift
Accelerate customer adoption
Requirements
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
Nice to have: customer-facing
Nice to have: startup
Nice to have: building or deploying AI/ML applications in production
Nice to have: founder or engineering lead experience
health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
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