Jobs in the United States

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Added 5 hours ago
Perception Engineer (Technical Lead, Engineering) - 30883
HII
Virginia Beach, VA
…Evaluate performance through robot testing, sea trials, and data analysis, turning findings into system improvements • Define metrics and evaluation frameworks to monitor deployed system…
Added 16 hours ago
Principal Hardware Engineer
Cisco Systems, Inc.
San Jose, CA
Bachelor’s degree in electrical engineering or computer engineering or computer science, with 15+ years of experience; master’s degree with 12+ years in electrical engineering or computer…
Added 19 hours ago
Senior AI/ML Research Engineer, Cloud AI Research and AI Rapid Response
Google
Mountain View, CA
Experience independently driving engineering delivery in rapid SWAT, Pathfinding, or Forward Deployed Engineering (FDE) environments.
Added 1 day ago
S
Senior Applied AI Engineer II
Saint-Gobain
NORTHBORO, MA
- $102,000 to $158,000 USD / year
This hands-on, forward-deployed role brings together scientists, engineers, industrial teams, business stakeholders, IT, data, MLOps, cybersecurity, architecture, and platform teams. It…
Added 1 day ago
Forward Deployed Engineer, AWS Forward Deployed Engineering, US Government
Amazon
Denver, CO
A Forward Deployed Engineer II (FDE II) embeds directly inside a strategic enterprise customer to independently design, build, deploy, and run AI-powered production systems alongside the…
Added 1 day ago
ID
Senior Cloud & Hybrid Network Engineer - JobID-0265
Innovative Defense Technologies
Arlington, VA
- $135,000 to $273,000 USD / year
…Artificial Intelligence (AI) & Machine Learning (ML) based data analytics, cybersecurity, as well as backfit and forward-fit tactical…
Added 1 day ago
TT
Founding Forward Deployed Engineer
True Talent Solutions Partners
Chicago, IL
- $200,000 to $250,000 USD / year
- Help establish the forward deployed engineering function as the team grows.
Added 1 day ago
Forward Deployed Engineer - Finance
NVIDIA USA
CA
NVIDIA Finance is hiring a Forward Deployed Engineer and AI Enabling expert to help turn that potential into measurable business outcomes. Embedded within the Finance AI team, you will work…
Added 1 day ago
Staff Site Reliability Engineer
Anduril Industries
Costa Mesa, CA
It drives CorpTech engineering forward through strategic investment in data platforms, software platforms, QA and release excellence, ERP engineering, and AI infrastructure.
Added 1 day ago
Senior Forward Deployed Software Engineer - Equities Technology
Millennium
Miami · New York
6+ years of professional software development experience, with a strong foundation in computer science principles including data structures, algorithms, and system design.
Added 1 day ago
Perception Engineer (Technical Lead, Engineering) - 30883
Huntington Ingalls Industries
Virginia Beach, VA
…Evaluate performance through robot testing, sea trials, and data analysis, turning findings into system improvements • Define metrics and evaluation frameworks to monitor deployed system…
Added 1 day ago
Lead Engineer, Pricing & Decision Systems
One Park Financial
Miami, FL
…accurately and on time. You will coordinate across Product, DevOps, Data Engineering, Data Science, and QA to take pricing changes from a specification to production with…
Added 1 day ago
Lead Engineer, Pricing & Decision Systems
One Park Financial
Plano, TX
…accurately and on time. You will coordinate across Product, DevOps, Data Engineering, Data Science, and QA to take pricing changes from a specification to production with…
Added 1 day ago
Lead Engineer, Pricing & Decision Systems
One Park Financial
Salt Lake City, UT
…accurately and on time. You will coordinate across Product, DevOps, Data Engineering, Data Science, and QA to take pricing changes from a specification to production with…
Added 1 day ago
Senior Data Scientist
Mphasis Corporation
NEW YORK, NY
Senior Data ScientistJob Title: Senior Data ScientistLocation:United States (US time zones)Experience: 4+ years of applied data science delivery## About the RoleYou will work as a forward…
Added 1 day ago
Staff AI Solutions Engineer - Nuclear & Safety
Mirion
Meriden, CT
…for visual inspection and image-based QA, spectral and sensor-data analytics, basic software development, and agentic AI / LLM-based automation for decision support and workflow…
Added 1 day ago
Forward Deployed AI Engineer Sr - Analytics
Dayforce
United States
As a Forward Deployed AI Engineer, you will work independently on a diverse set of well-defined and emerging problems, using sound judgment to adapt established engineering patterns to the…
Added 1 day ago
Forward Deployed AI Engineer Sr - Analytics
Dayforce
United States
As a Forward Deployed AI Engineer, you will work independently on a diverse set of well-defined and emerging problems, using sound judgment to adapt established engineering patterns to the…
Added 1 day ago
Principal AI Platform Engineer
ServiceNow
Santa Clara, CA
…automation, CPQ, customer service, and field service. As Principal Forward Deployed Engineer, you are the lead architect for the FDE group within CRM & Industry Engineering: the person who…
Added 1 day ago
Forward Deployed Engineer (Model Customization and Optimization), AWS Forward Deployed Engineering
Amazon Web Services, Inc.
Boston, MA · Arlington, VA · Seattle, WA · New York, NY · East Palo Alto, CA
As a Forward Deployed Engineer II (FDE II) on the Custom Model and Optimization team, you embed directly with strategic customers to build, optimize, and run custom generative AI models in…
Added 1 day ago
Senior Forward Deployed Engineer (Model Customization and Optimization)
Amazon Web Services, Inc.
Boston, MA · Arlington, VA · Seattle, WA · New York, NY · East Palo Alto, CA
As a Senior Forward Deployed Engineer (Senior FDE) on the Custom Model and Optimization team, you are the technical lead embedded inside a strategic customer, accountable for building,…
Added 1 day ago
SH
Product Engineer - AI/ML
Stanford Health Care
United States
- $81.59 to $108.12 USD / hour
The Product Engineer – AI/ML bridges technical strategy, hands-on software development, and applied AI delivery. Operating in a forward-deployed capacity, this role works directly with…
Added 2 days ago
Staff Data Scientist, Forward Deployed
6sense
San Francisco, CA
Forward Deployed Engineering (FDE), Predictive track, in Data Science & AI Engineering
Added 2 days ago
Sr. ML Ops Engineer, Forward-Deployed
6sense
San Francisco, CA
Forward Deployed Engineering (FDE), Predictive track, in Data Science & AI Engineering
Added 2 days ago
Director, Solutions Engineer Forward Deployed - Splunk (Remote)
Cisco
New York, NY
The Cisco-Splunk Forward Deployed Solutions Engineering (FDSE) team is an elite, hands-on technical organization that embeds directly alongside our most strategic global customers across…

Dayforce

Forward Deployed AI Engineer Sr - Analytics

United States

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Job details

Posting language: English
Posted: Oct 25, 2026

Original job description

Dayforce is a global human capital management (HCM) company headquartered in Toronto, Ontario, and Minneapolis, Minnesota, with operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan (APJ) region.

Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce.

Our brand promise - Makes Work Life Better™ - Reflects our commitment to employees, customers, partners and communities globally.

About the opportunity

We are looking for a Senior Forward Deployed AI Engineer, Analytics to partner directly with analytics teams and business stakeholders to turn high-value analytical problems into practical, trustworthy AI solutions. This hands-on role helps move the organization beyond static dashboards toward conversational analytics, intelligent insights, and AI-enabled decision support.

As a Forward Deployed AI Engineer, you will work independently on a diverse set of well-defined and emerging problems, using sound judgment to adapt established engineering patterns to the needs of each use case. You will prototype, validate, deploy, and improve solutions in partnership with the Enterprise AI Platform, Decision Intelligence, Data Engineering, Architecture, and Governance teams. Success is measured by user trust, adoption, and measurable business value.

What you’ll get to do

Forward Deployed AI Engineering

Partner directly with analytics and business teams to understand decisions, workflows, pain points, and analytical questions that AI can help address.
Translate business needs into clear technical requirements, solution designs, prototypes, and production-ready AI experiences.
Independently deliver assigned AI use cases from discovery through user validation, deployment, and ongoing improvement, escalating material architecture, security, or platform decisions when needed.
Use feedback and usage data to improve solution accuracy, relevance, reliability, and adoption.
Recommend simpler alternatives, including BI, analytics, automation, or workflow improvements, when AI is not the best fit.

AI-Powered and Conversational Analytics

Build conversational analytics experiences that allow authorized users to ask natural-language questions of trusted enterprise data.
Develop AI assistants and agentic workflows that retrieve business context, query governed analytical data, interpret results, and provide understandable responses.
Build capabilities that identify trends, anomalies, risks, opportunities, and recommended actions under established business and technical guardrails.
Integrate AI-generated insights into existing analytics tools, applications, and workflows so they are available where decisions are made.
Apply judgment to determine when predictive analytics, generative AI, agents, or a combination of approaches is appropriate.

Enterprise Context and Semantic Intelligence

Use semantic models, business definitions, metrics, metadata, and relationships to ground AI solutions in trusted enterprise context.
Implement retrieval and context patterns across structured data, documents, knowledge bases, and approved enterprise information sources.
Work with data architects, governance specialists, and analytics teams to identify gaps in data quality, semantic clarity, lineage, or access that affect AI reliability.
Ensure AI responses can be traced to appropriate enterprise data sources and business definitions when required.

Agentic Analytics Engineering

Develop AI agents and workflows using approved orchestration frameworks, enterprise AI services, APIs, and data platforms.
Implement tool calling, retrieval-augmented generation, vector or semantic retrieval, and secure API or MCP integrations using established enterprise patterns.
Enable agents to interact securely with semantic models, datasets, knowledge sources, and enterprise services within a user’s authorized access.
Apply appropriate human review and approval controls for high-impact insights, recommendations, and actions.

Prototype to Production Delivery

Rapidly build and test prototypes to validate user value, feasibility, and trust before broader investment.
Define and measure practical success criteria such as response quality, adoption, productivity, decision cycle time, or business impact.
Engineer approved solutions for production reliability, scalability, security, observability, and supportability using enterprise standards.
Develop automated tests and evaluation scenarios for AI-generated responses, including analytical accuracy, grounding, and relevance.
Monitor solution performance, latency, cost, failures, feedback, and adoption; diagnose issues and implement improvements within established support practices.

Governance and Platform Partnership

Use enterprise-approved models, platforms, security patterns, connectors, and reusable components rather than creating isolated point solutions.
Apply established Responsible AI, privacy, security, data governance, identity, and authorization requirements throughout solution delivery.
Partner with Enterprise AI Platform, Security, Privacy, Legal, and Data Governance teams to address exceptions, risks, and complex integration needs.
Document reusable implementation patterns and provide feedback from deployments to improve shared platform capabilities and standards.
Communicate technical options, tradeoffs, progress, and risks clearly to technical and business partners; advise stakeholders on difficult implementation matters within the role’s area of expertise.

Skills and experience we value

Typically 5 or more years of related experience with a Bachelor’s degree, 3 or more years with a Master’s degree, or equivalent practical experience in software engineering, data engineering, analytics engineering, AI or ML engineering, data science, or a related field.
Hands-on experience building and deploying production data, analytics, AI, or Generative AI solutions.
Strong Python, SQL, and software engineering skills, including APIs, testing, version control, and CI/CD practices.
Working knowledge of LLMs, retrieval-augmented generation, AI agents, tool calling, embeddings, vector search, semantic retrieval, and enterprise knowledge integration.
Experience with one or more enterprise AI services or platforms such as Azure AI Foundry, Azure OpenAI, OpenAI, Anthropic, or comparable technologies.
Experience working with analytical data platforms, warehouses or lakehouses, semantic models, APIs, and BI technologies such as Microsoft Fabric, Power BI, Databricks, Snowflake, or equivalent.
Understanding of semantic and dimensional modeling, business metrics, metadata, data quality, lineage, and governed data access.
Experience applying authentication, authorization, RBAC, identity propagation, and secure access practices to AI or data solutions.
Understanding of LLMOps or MLOps concepts, including deployment, evaluation, monitoring, observability, and production support.
Ability to work independently through diverse technical problems, adapt established approaches when appropriate, and seek guidance at key decision points.
Strong communication and collaboration skills, including the ability to work effectively with senior business and technical stakeholders.

What would make you stand out

You have taken an AI or analytics solution from business discovery through prototype, user testing, production deployment, and adoption.
You can work comfortably with both business stakeholders and technical teams, translating between decisions, data, and implementation details.
You have built conversational analytics or AI-enabled decision support on top of governed enterprise data.
You understand why semantic context, data quality, lineage, and access controls are essential to trustworthy enterprise AI.
You are pragmatic about using the simplest technology that solves the business problem and can explain tradeoffs clearly.
You share lessons learned and reusable patterns that help other teams deliver AI solutions more effectively.

What’s in it for you

Dayforce is fueled by the diversity of our talented employees. We are an equal opportunity employer and consider and embrace ALL individuals and what makes them unique. We believe our employees should be happy and healthy, with peace of mind and a sense of fulfillment.

We encourage individuals to apply based on their passions.

Dayforce employees and their families are eligible to participate in the following benefits programs: medical, dental, vison, and life insurance. Dayforce employees are also eligible to participate in a 401k plan (plus match). Employees also receive unlimited Time Away From Work (in lieu of accrued vacation time), 10 paid US holidays, up to 80 hours of paid sick time and 17 weeks of paid parental leave, subject to the terms of the applicable policy or program.

With a commitment to community impact, including volunteer days and our charity, Dayforce Cares we provide opportunities for you to thrive both in your career and personal life. Our focus is not just on your job but on supporting you to be the best version of yourself.

About the Salary Ranges

Please note that the salary range mentioned in this job description should serve simply as a guide. The final compensation offered may vary based on a variety of factors, including bonuses and/or incentives, or a candidate’s experience, skills, budget and location. Our company is committed to providing a fair, equitable, and competitive package that reflects the value an individual brings to the organization.

Fraudulent Recruiting

Beware of fraudulent recruiting. Legitimate Dayforce contacts will use an @dayforce.com email address. We do not request money, checks, equipment orders, or sensitive personal data during the recruitment process. If you have been asked for any of the above, or believe you have been contacted by someone posing as a Dayforce employee, please refer to our fraudulent recruiting statement found here: https://www.dayforce.com/be-aware-of-recruiting-fraud

Dayforce actively monitors all job applications to ensure authenticity. Submissions determined to be fraudulent or misleading will be declined from the recruitment process

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