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Forward Deployed Engineer Senior Manager \| Senior Level \| Full time
Job No. R00341833 \| Multiple Locations
We Are
Accenture is building a new portfolio of agentic software products in the industries we have spent decades helping to transform. We begin with advantages most product companies do not have: deep industry expertise, trusted relationships with many of the world’s largest organizations, and direct access to the complex workflows and problems that matter most to them. That allows us to build closely with customers while creating repeatable products that can be taken broadly to market.
We are forming small, highly capable product teams to do this. These teams bring product management, design, and engineering together with the autonomy to move quickly, make decisions, and own outcomes from the earliest prototype through production and scale.
This is a software engineering role within a permanent product team. It is not a consulting delivery, data engineering, product management, or forward\-deployed engineering role.
You Are
You are an exceptional AI\-native software engineer who has built and shipped production products across the full stack. You combine strong engineering fundamentals with product judgment, systems thinking, and a high bar for quality. You are comfortable beginning with an ambiguous customer or business problem, shaping the technical approach, and turning it into software that real users rely on.
AI is central to both what you build and how you build. You use coding agents and other AI development tools as a core part of your daily workflow. You know how to decompose work, provide the right context and constraints, establish tests and evaluations, and review generated output with rigor. You use AI to increase your leverage while retaining full accountability for the architecture, security, reliability, and quality of the product.
You are energized by zero\-to\-one work, small teams, high autonomy, and the opportunity to help define how a new product engineering organization should operate.
What You Will Do
Build and ship across the full stack. Own meaningful product capabilities end to end, including application architecture, data models, backend services, APIs, integrations, AI systems, and user experiences. Work directly with product managers and designers to turn customer problems into simple, high\-quality products. Move comfortably between prototyping and production engineering, making thoughtful decisions about when to optimize for speed and when to invest for scale, security, and reliability.
Build AI\-native products. Design and implement agentic systems, including model interactions, tool use, retrieval, orchestration, state management, evaluations, observability, and guardrails. Build products that perform reliably against complex, real\-world industry workflows rather than only in controlled demonstrations. Evaluate model and system behavior rigorously, understand failure modes, and improve the product through evidence.
Work in an AI\-native engineering model. Use coding agents and AI development tools extensively throughout the engineering lifecycle. Create the context, specifications, tests, development environments, CI pipelines, and evaluation systems that allow agents to produce high\-quality work safely and efficiently. Direct multiple streams of agent\-assisted work where appropriate, review outputs critically, and remain accountable for everything that reaches production.
Set technical direction. Translate ambiguous product opportunities into clear technical approaches and executable plans. Make sound architecture decisions for new product areas and carry those decisions from prototype through production. Balance speed, simplicity, extensibility, security, cost, and operational reliability. Identify where the team should build, buy, integrate, or deliberately defer.
Own product and production outcomes. Stay close to users and customers and understand the workflows your software is changing. Use customer feedback, product data, evaluations, and operational signals to improve the product continuously. Own reliability, observability, security, performance, and maintainability in production. Treat successful adoption and customer outcomes as engineering concerns.
Raise the engineering bar. Provide rigorous technical review on the work that matters most. Help other engineers improve their judgment, execution, and use of AI\-native development practices. Contribute to the shared architecture, tools, standards, and operating practices of the broader product engineering organization. Help define how small, AI\-native product teams should work as the company grows.
This role is a hybrid role and will require onsite work in Seattle, New York, and/or Mountain View office and can include travel (0\-100%).
What You Bring
- Minimum of 8 years eight years of experience building and shipping production software.
- Minimum of 8 years experience building across the full stack, including frontend and backend systems.
- Minimum of 8 years software engineering fundamentals, including system design, data modeling, APIs, testing, cloud\-native development, security, observability, and production operations.
- Minimum 2 years of substantive, hands\-on AI\-native engineering experience as part of your day\-to\-day work. This may include building with LLM APIs, coding agents, agent frameworks, tool integrations, retrieval systems, evaluation frameworks, or production guardrails.
- Minimum 1 years experience building reliable AI or agentic systems that operate beyond a prototype or demonstration environment including a track record of taking products, systems, or major capabilities from zero to one and owning them through production.
- Demonstrated ability to use AI development tools to materially increase engineering leverage without lowering the quality bar.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience.
Required Professional Skills:
- Excellent judgment under ambiguity and the ability to make progress without complete information.
- Strong product instincts and the ability to recognize what makes a product useful, intuitive, and well crafted.
- The ability to communicate technical decisions clearly and work closely with product managers, designers, customers, and domain experts.
- The ability to communicate technical decisions clearly and work closely with product managers, designers, customers, and domain experts.
- A genuine interest in frontier AI and a consistent habit of testing new models, tools, and engineering approaches in practice.
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.
We anticipate this job posting will be posted until 09/03/2026\.
Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long\-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here:
U.S. Employee Benefits \| Accenture
Role Location Annual Salary Range
California $132,500 to $366,300
Cleveland $122,700 to $293,000
Colorado $132,500 to $316,400
District of Columbia $141,100 to $337,000
Illinois $122,700 to $316,400
Maine $112,900 to $269,600
Maryland $132,500 to $316,400
Massachusetts $132,500 to $337,000
Minnesota $132,500 to $316,400
New York $122,700 to $366,300
New Jersey $141,100 to $366,300
Virginia $122,700 to $337,000
Washington $141,100 to $337,000
Seattle, WA
Mountain View, CA
New York City, NY
San Francisco, CA
Requesting an Accommodation
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If you would like to be considered for employment opportunities with Accenture and have accommodation needs such as for a disability or religious observance, please call us toll free at 1 (877\) 889\-9009 or send us an email or speak with your recruiter.
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Accenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities.
Accenture is committed to providing veteran employment opportunities to our service men and women.
Other Employment Statements
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Further, at Accenture a criminal conviction history is not an absolute bar to employment.
The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.
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Salary Context
This $122K-$337K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $183K across 194 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Logic, Inc., this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills in Demand for This Role
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $219,250 based on 424 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($229K) sits 5% above the category median. Disclosed range: $122K to $337K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Logic, Inc. AI Hiring
Logic, Inc. has 17 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, AI Architect. Positions span Seattle, WA, US, New York, NY, US, Columbus, OH, US. Compensation range: $205K - $387K.
Location Context
AI roles in Seattle pay a median of $236,900 across 267 tracked positions. That's 9% above the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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