Forward Deployed AI Scientist Jobs
Forward Deployed AI Scientist jobs are open across enterprise software, defense, fintech, and healthcare, from early-career to staff and principal levels, with specializations in model deployment, MLOps, and customer-facing AI solutions. Find a role that fits below and apply directly.
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DESCRIPTION
AWS is seeking a Sr. Technical Business Development Manager to own the go-to-market strategy that gives a fast-growing forward deployed engineering (FDE) organization durable access to the engineers it needs to grow. Forward deployed engineers pair deep production software experience with direct customer engagement: they work alongside customers to solve complex technical problems, build production solutions, and turn emerging technology into scalable outcomes. The market for this talent is specialized and competitive, and winning in it requires a deliberate strategy, real investment, and subject matter fluency in the work itself.
You will own that strategy end to end. You will build a fact-based view of the talent market, define where AWS should compete and invest, and develop the business cases, investment proposals, and executive narratives that fund and direct that work. You will structure and manage a portfolio of external relationships, with technical communities, professional networks, industry groups, and conference organizations, as channels that give AWS credible access to experienced engineers. You will carry measurable goals for qualified pipeline, orchestrate delivery across engineering, marketing, communications, events, finance, legal, and Talent Acquisition without direct authority, and use market and conversion data to decide where to expand, redirect, or exit. You own the strategy and the business outcome; partner teams run execution and operations, and Talent Acquisition owns candidate outreach, assessment, and hiring at the downstream hand-off.
This role requires technical fluency in forward deployed engineering and the AI and cloud landscape, strong business judgment, and the ability to create clarity in an ambiguous environment where strategy, plan, and stakeholders are not predefined. You will advise senior leaders, negotiate and structure external engagements, and align teams you do not own. Travel: 30 to 50%.
Key job responsibilities
Own the go-to-market strategy for building durable access to forward deployed engineering talent. Translate the organization's growth plans and engineering needs into where AWS competes, which segments to prioritize, and how to allocate investment.
Build a fact-based view of the talent market: concentration, candidate motivations, competitive dynamics, geography, and emerging sources of qualified engineers.
Develop the external value proposition for FDE opportunities at AWS, grounded in technical credibility with experienced engineering audiences.
Build business cases, investment proposals, and operating plans for new pipeline initiatives, and carry the goals and performance measures that judge their return.
Structure and manage a portfolio of external relationships (technical communities, professional networks, industry groups, conference organizations) as channels for reaching relevant engineers. Negotiate the terms and model of AWS participation.
Orchestrate delivery across engineering, marketing, communications, events, finance, legal, operations, and Talent Acquisition, owning the business outcome while partner teams run execution.
Establish the mechanisms that connect external engagement to the recruiting process: shared goals, pipeline attribution, feedback loops, and operating rhythms with partner teams.
Measure market reach, audience quality, qualified pipeline, program efficiency, and conversion. Recommend where AWS should expand, redirect, replicate, or discontinue investment.
Identify repeatable, scalable approaches that extend across technical disciplines, markets, and business teams while holding AWS's quality bar.
Advise senior leaders on market position, pipeline strategy, investment requirements, and risks to the growth plan. Represent AWS credibly with technical leaders, engineering communities, and executive audiences.
A day in the life
Your work centers on how AWS builds sustained access to the specialized talent forward deployed engineering depends on. You will work with FDE leaders to understand growth plans, technical priorities, and future capability needs, then translate those into a market strategy, an investment thesis, and a portfolio of initiatives. Much of the role is strategic and deal-oriented: you might decide AWS should compete in a specific engineering community, build the business case for a flagship initiative around an emerging discipline, and negotiate the terms of AWS's participation with an external organization. You will define the audience and business outcome, secure investment, align contributors across the org, and set the goals and quality bar, while partner teams handle delivery and logistics. You will track portfolio performance and shifts in the AI and engineering talent market, use pipeline and conversion insight to see which markets and initiatives produce the strongest return, and advise senior leaders on opportunities, investment choices, and risks. Success is whether your strategy creates a scalable, durable source of qualified forward deployed engineering talent.
About the team
You will support a growing AWS engineering organization that builds and deploys production solutions for complex customer challenges. Its forward deployed engineers combine deep technical expertise with close customer collaboration, working across disciplines to turn ambitious ideas and emerging technology into real-world outcomes in a space shaped by rapid advances in AI, cloud, and modern software development. Its growth depends on attracting engineers who can pair technical delivery with customer engagement and business ownership, and this role owns the market strategy and investment that make that access possible.
BASIC QUALIFICATIONS
- 5+ years of developing, negotiating and executing business agreements experience
- 5+ years of Go-To-Market, Business Development, Sales, or Consulting experience
- 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML (Artificial Intelligence/Machine Learning), GenAI (Generative AI), Analytics, Database, and/or Storage experience
- 5+ years of in program management, workforce strategy development, or metrics-driven decision making experience
- Bachelor's degree
- Experience explaining complex technical concepts to various business and technical audiences
PREFERRED QUALIFICATIONS
- Master's degree in business, data science, public administration, finance, engineering, human resources, or related field, or PMP certificate
- Experience interpreting data and making business recommendations
- Experience identifying, negotiating, and executing complex legal agreements
- Experience designing, implementing, and scaling workforce development programs across large-scale operations, including forecasting workforce needs and leveraging analytics to drive program decisions
- Experience interpreting data and making business recommendations across leadership and cross-functional teams
- Experience using analytical tools for workforce metrics and reporting
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, MA, Boston - 147,900.00 - 200,100.00 USD annually
USA, NY, New York - 162,700.00 - 220,200.00 USD annually
USA, TX, Dallas - 147,900.00 - 200,100.00 USD annually
USA, VA, Arlington - 147,900.00 - 200,100.00 USD annually
USA, WA, Seattle - 147,900.00 - 200,100.00 USD annually
DESCRIPTION
AWS is seeking a Sr. Technical Business Development Manager to own the go-to-market strategy that gives a fast-growing forward deployed engineering (FDE) organization durable access to the engineers it needs to grow. Forward deployed engineers pair deep production software experience with direct customer engagement: they work alongside customers to solve complex technical problems, build production solutions, and turn emerging technology into scalable outcomes. The market for this talent is specialized and competitive, and winning in it requires a deliberate strategy, real investment, and subject matter fluency in the work itself.
You will own that strategy end to end. You will build a fact-based view of the talent market, define where AWS should compete and invest, and develop the business cases, investment proposals, and executive narratives that fund and direct that work. You will structure and manage a portfolio of external relationships, with technical communities, professional networks, industry groups, and conference organizations, as channels that give AWS credible access to experienced engineers. You will carry measurable goals for qualified pipeline, orchestrate delivery across engineering, marketing, communications, events, finance, legal, and Talent Acquisition without direct authority, and use market and conversion data to decide where to expand, redirect, or exit. You own the strategy and the business outcome; partner teams run execution and operations, and Talent Acquisition owns candidate outreach, assessment, and hiring at the downstream hand-off.
This role requires technical fluency in forward deployed engineering and the AI and cloud landscape, strong business judgment, and the ability to create clarity in an ambiguous environment where strategy, plan, and stakeholders are not predefined. You will advise senior leaders, negotiate and structure external engagements, and align teams you do not own. Travel: 30 to 50%.
Key job responsibilities
Own the go-to-market strategy for building durable access to forward deployed engineering talent. Translate the organization's growth plans and engineering needs into where AWS competes, which segments to prioritize, and how to allocate investment.
Build a fact-based view of the talent market: concentration, candidate motivations, competitive dynamics, geography, and emerging sources of qualified engineers.
Develop the external value proposition for FDE opportunities at AWS, grounded in technical credibility with experienced engineering audiences.
Build business cases, investment proposals, and operating plans for new pipeline initiatives, and carry the goals and performance measures that judge their return.
Structure and manage a portfolio of external relationships (technical communities, professional networks, industry groups, conference organizations) as channels for reaching relevant engineers. Negotiate the terms and model of AWS participation.
Orchestrate delivery across engineering, marketing, communications, events, finance, legal, operations, and Talent Acquisition, owning the business outcome while partner teams run execution.
Establish the mechanisms that connect external engagement to the recruiting process: shared goals, pipeline attribution, feedback loops, and operating rhythms with partner teams.
Measure market reach, audience quality, qualified pipeline, program efficiency, and conversion. Recommend where AWS should expand, redirect, replicate, or discontinue investment.
Identify repeatable, scalable approaches that extend across technical disciplines, markets, and business teams while holding AWS's quality bar.
Advise senior leaders on market position, pipeline strategy, investment requirements, and risks to the growth plan. Represent AWS credibly with technical leaders, engineering communities, and executive audiences.
A day in the life
Your work centers on how AWS builds sustained access to the specialized talent forward deployed engineering depends on. You will work with FDE leaders to understand growth plans, technical priorities, and future capability needs, then translate those into a market strategy, an investment thesis, and a portfolio of initiatives. Much of the role is strategic and deal-oriented: you might decide AWS should compete in a specific engineering community, build the business case for a flagship initiative around an emerging discipline, and negotiate the terms of AWS's participation with an external organization. You will define the audience and business outcome, secure investment, align contributors across the org, and set the goals and quality bar, while partner teams handle delivery and logistics. You will track portfolio performance and shifts in the AI and engineering talent market, use pipeline and conversion insight to see which markets and initiatives produce the strongest return, and advise senior leaders on opportunities, investment choices, and risks. Success is whether your strategy creates a scalable, durable source of qualified forward deployed engineering talent.
About the team
You will support a growing AWS engineering organization that builds and deploys production solutions for complex customer challenges. Its forward deployed engineers combine deep technical expertise with close customer collaboration, working across disciplines to turn ambitious ideas and emerging technology into real-world outcomes in a space shaped by rapid advances in AI, cloud, and modern software development. Its growth depends on attracting engineers who can pair technical delivery with customer engagement and business ownership, and this role owns the market strategy and investment that make that access possible.
BASIC QUALIFICATIONS
- 5+ years of developing, negotiating and executing business agreements experience
- 5+ years of Go-To-Market, Business Development, Sales, or Consulting experience
- 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML (Artificial Intelligence/Machine Learning), GenAI (Generative AI), Analytics, Database, and/or Storage experience
- 5+ years of in program management, workforce strategy development, or metrics-driven decision making experience
- Bachelor's degree
- Experience explaining complex technical concepts to various business and technical audiences
PREFERRED QUALIFICATIONS
- Master's degree in business, data science, public administration, finance, engineering, human resources, or related field, or PMP certificate
- Experience interpreting data and making business recommendations
- Experience identifying, negotiating, and executing complex legal agreements
- Experience designing, implementing, and scaling workforce development programs across large-scale operations, including forecasting workforce needs and leveraging analytics to drive program decisions
- Experience interpreting data and making business recommendations across leadership and cross-functional teams
- Experience using analytical tools for workforce metrics and reporting
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, MA, Boston - 147,900.00 - 200,100.00 USD annually
USA, NY, New York - 162,700.00 - 220,200.00 USD annually
USA, TX, Dallas - 147,900.00 - 200,100.00 USD annually
USA, VA, Arlington - 147,900.00 - 200,100.00 USD annually
USA, WA, Seattle - 147,900.00 - 200,100.00 USD annually
Forward Deployed AI Scientist Jobs by Experience Level
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Find JobsForward Deployed AI Scientist Job Market
Who's Hiring
- Databricks69
- Amazon Web Services41
- Palantir Technologies40
- Deloitte35
- Accenture25
Top Industries Hiring
- Technology & Software189
- Consulting & Professional Services30
- Artificial Intelligence23
- Staffing & Recruiting14
- Accounting & Auditing8
What Employers Look For
The qualifications that appear most often in forward deployed AI scientist jobs.
- Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
- Hands-on experience deploying and maintaining machine learning models in production environments
- Ability to work directly with enterprise customers to scope, implement, and iterate on AI solutions
- Experience with cloud platforms such as AWS, Azure, or Google Cloud for model serving and monitoring
- Strong communication skills to explain model behavior and trade-offs to non-technical stakeholders
- Bachelor's or master's degree in computer science, machine learning, mathematics, or a related field
Tips for Your Forward Deployed AI Scientist Job Search
Tailor your resume to deployment depth
Hiring managers for this role care less about research publications and more about production impact. Quantify the scale of models you shipped, the latency improvements you drove, and the customer problems you solved end-to-end, not just trained.
Highlight cross-functional communication experience
Forward deployed roles sit at the intersection of engineering, product, and customer success. Your resume should show examples of translating technical constraints to non-technical stakeholders, since that skill separates candidates as much as any ML framework fluency.
Apply early to roles that fit
Migrate Mate lists forward deployed ai scientist openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target companies with active deployment teams
Focus your search on companies that publicly discuss embedded AI or on-site customer engineering. Job listings that mention 'customer environments', 'field deployment', or 'professional services' signal a genuine forward deployed function, not a rebranded research role.
Prepare a deployment war story for interviews
Interviewers will push past your model architecture knowledge to ask how you handled a failing deployment in a customer environment. Prepare a specific story covering the failure mode, your diagnostic approach, and what you changed to stabilize production.
Negotiate scope and travel expectations upfront
Many forward deployed positions involve significant on-site time with clients. Before accepting an offer, clarify the expected travel percentage, which geographies are covered, and whether remote deployment options exist for your target accounts.
Forward Deployed AI Scientist Jobs: Frequently Asked Questions
Which companies are hiring the most forward deployed ai scientists?
Databricks, Amazon Web Services, and Palantir Technologies are hiring the most forward deployed ai scientists right now, with openings concentrated in California, New York, and Texas, based on current listings on Migrate Mate as of November 2026. Demand is strongest at enterprise AI platforms and defense technology firms.
How many forward deployed ai scientist jobs are remote?
About 64% of forward deployed ai scientist openings are fully remote or hybrid as of November 2026, though the nature of the role means many positions require periodic on-site visits to client locations. Fully remote arrangements are most common for sub-roles focused on model evaluation, documentation, and async technical advisory work.
How do you become a forward deployed ai scientist?
Start by building a foundation in machine learning engineering, including model training, evaluation, and production deployment. Gain experience working directly with external stakeholders, ideally through customer-facing engineering or technical solutions roles. Develop proficiency in cloud-based serving infrastructure, then target companies that run embedded AI programs or field deployment teams. A portfolio demonstrating shipped, monitored, and iterated production models is more persuasive than research credentials alone.
Can you get a forward deployed ai scientist job with little experience?
Entry points exist, but they typically require demonstrating deployment instincts rather than seniority. Building open-source projects that go beyond notebooks into packaged, served APIs shows production mindset. Roles titled 'associate solutions engineer' or 'AI implementation specialist' often serve as the on-ramp before a formal forward deployed title is attached. Customer-facing internships at AI companies are another common path in.
What does the forward deployed ai scientist interview process look like?
Most processes include an initial screening call, a technical assessment covering ML fundamentals and system design, and a customer simulation or case study round where you diagnose a fictional deployment problem. Final rounds typically involve a presentation to a cross-functional panel assessing both technical depth and communication clarity. Some employers also include a brief on-site exercise simulating a client kickoff meeting.
Where can I find and apply to forward deployed ai scientist jobs?
You can find and apply to forward deployed ai scientist jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience and apply directly to each listing.
See All 1,204+ Forward Deployed AI Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
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