Senior Advanced AI Research Engineer

Accenture PLC; Mountain View (CA); On-site; USD 133,000 - 338,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) plan

Paid holidays and PTO

Job summary

Accenture is seeking a Senior Advanced AI Research Engineer in Mountain View, CA, to bridge AI research and production platform engineering. You will explore agentic AI frontiers, develop prototypes, and deliver platform-ready capabilities that scale across workloads.

You will write research artefacts and production code in the same week, fluent in Python and TypeScript, and collaborate with engineers, PMs, and architects to align research with client deployment needs.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field.
• 5+ years of experience with Python and/or Node.js/TypeScript, building and shipping production backend services.
• 5+ years of hands-on experience with AI/ML systems such as LLMs, agent frameworks, or retrieval/memory architectures.
• Bonus points for 6+ years across both research and production contexts with published artefacts.
• Deep expertise in applied AI systems research, including memory, routing, autonomy, or evaluation.
• 3+ years translating research findings into platform-integrated artefacts or open-source contributions.
• Hands-on experience with async Python, containers, Kubernetes, databases, and tracing instrumentation.

Responsibilities

• Applied Research & Innovation on agentic AI frontiers and benchmarking for real workloads.
• Translational Engineering: turn research into production-grade Python services and SDK modules.
• Prototype and validate platform components with observable metrics and low-friction integration.
• Collaborate with platform engineers to ensure production standards and test coverage.
• Communicate results clearly to technical and non-technical stakeholders; mentor juniors.

Skills

Python

Node.js/TypeScript

AI/ML systems

FastAPI/async Python

Kubernetes

OpenTelemetry

Vector databases

Distributed tracing

Education

Bachelor's degree in CS/CE or related

Master's or PhD preferred

Tools

FastAPI

Kubernetes

OpenTelemetry

TypeScript

Node.js

Job description

We Are:We are at the forefront of a new era in enterprise AI — one defined not by model capability alone, but by the infrastructure, memory systems, and routing intelligence required to make autonomous AI agents trustworthy and commercially viable at scale. Our Data & AI practice brings together more than 45,000 professionals helping clients design, deploy, and govern AI systems across regulated industries. Our applied research function sits at the intersection of frontier AI research and production engineering — investigating the foundational challenges that will determine whether enterprise agentic AI succeeds or stalls.

You Are:

As a Senior Advanced AI Research Engineer, you sit at the boundary between AI systems research and production platform engineering. You investigate hard, open problems in agentic AI — and you close the loop: turning research findings into engineered prototypes, then into platform‑ready capabilities that real workloads depend on. You are a strong Python engineer who can move fluently between an experiment and a well‑structured service or SDK module. You write research artefacts and production code in the same week, and you understand why both matter.

The Work

• Applied Research & Innovation: Investigate active innovation frontiers in agentic AI systems — for example, agent memory and knowledge persistence architectures, model selection and inference routing strategies, autonomy and goal‑anchoring control planes, and long‑horizon task reliability. The specific focus areas evolve with client demand and research opportunity. Design and execute rigorous benchmarking and evaluation methodologies scoped to production‑relevant agentic task profiles — covering dimensions such as tool use, structured output generation, multi‑step reasoning, instruction following, and failure recovery. Investigate efficiency and scalability frontiers — such as inference cost reduction, context management at scale, and retrieval architecture design — that determine whether agent workloads can be served commercially on attainable hardware. Contribute to external publications, technical reports, and conference submissions that establish thought leadership and build the evidence base for client and platform decisions.
• Translational Engineering: Translate research findings into production‑grade implementations: engineered Python services, Node.js/TypeScript SDK modules, or platform‑integrated components that other engineers and agent workloads depend on. Build well‑defined provider interfaces and pluggable backends for research components — memory stores, retrieval layers, routing modules — so that experimental implementations can be iterated on and swapped independently of the platform code that depends on them. Prototype and validate platform‑level capabilities — such as inference routing policies, memory management layers, or agent control mechanisms — and carry them through from experiment to integrated, observable system component. Instrument research prototypes with observability from the start — distributed tracing, cost accounting, and latency metrics — so findings are reproducible and platform integration is low‑friction.
• Platform Contribution & Integration: Work alongside platform engineers to integrate validated research capabilities into production systems — contributing well‑tested, documented Python and Node.js/TypeScript code through standard engineering workflows including code review, CI, and schema validation. Identify platform gaps surfaced by research experiments — missing APIs, insufficient observability, constrained interfaces — and raise them as concrete, scoped engineering proposals. Ensure that research‑derived capabilities meet production standards: correct error handling, sensible defaults, documented contracts, and test coverage appropriate to their risk profile.
• Collaboration & Communication: Work closely with platform engineers, product managers, and enterprise architects to align research priorities with real client deployment blockers and platform roadmap needs. Communicate research findings, architectural trade‑offs, and prototype results clearly to both technical peers and non‑technical stakeholders — in written artefacts, design reviews, and client‑facing sessions. Mentor junior engineers and researchers on experimental methodology, translational engineering practices, and production‑quality code standards.
• Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements. This role requires working onsite in Mountain View, CA. Applicants must be local or willing to relocate to Mountain View area prior to joining.

Here’s what you need

Bachelor's degree (or equivalent minimum 12 years work experience, or minimum 6 years' work experience with Associate's degree) in Computer Science, Computer Engineering, or a related field.

Minimum of 5 years of experience with Python and/or Node.js/TypeScript, building and shipping production backend services, research prototypes, or AI/ML systems.

Minimum of 5 years of hands‑on experience with AI or ML systems — such as large language models, agent frameworks, inference serving, or retrieval and memory architectures.

Bonus points if you have 6+ years of engineering experience across both research and production contexts, with a demonstrated ability to ship research into running systems.

Deep experience in at least one area of applied AI systems research — such as agent memory and knowledge management, inference efficiency and model routing, agentic evaluation methodology, or long‑horizon task and autonomy research.

3+ years of applied research with a track record of translating findings into platform‑integrated or published artefacts — prototypes, open‑source contributions, internal frameworks, or peer‑reviewed papers.

Hands‑on experience with async Python (e.g. FastAPI, asyncio), containerisation and Kubernetes, vector and relational databases, and distributed tracing instrumentation (e.g. OpenTelemetry).

Familiarity with modern AI agent framework ecosystems and agent communication protocols — the specific tools matter less than the ability to work across multiple frameworks and evaluate them critically.

Master's or PhD in Computer Science, Computer Engineering, or a related field is strongly preferred.

Compensation

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 08/31/2026.

Benefits

• 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.

Annual Salary Range

• California $132,500 to $338,300
• Colorado $132,500 to $292,200
• Connecticut $132,500 to $292,200
• District of Columbia $141,100 to $311,200
• Illinois $122,700 to $292,200
• Maine $112,900 to $249,000
• Maryland $132,500 to $292,200
• Massachusetts $132,500 to $311,200
• Minnesota $132,500 to $292,200
• New York $122,700 to $338,300
• New Jersey $141,100 to $338,300
• Ohio $122,700 to $270,600
• Virginia $122,700 to $311,200
• Washington $141,100 to $311,200

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us at www.accenture.com

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Bring your incredible skills and join our global team of innovators. We come together from different backgrounds across the world and work with the latest technologies to create value and growth for our clients. With us, you’ll continue to learn and grow so you can advance in your career. Your personal dreams and ambitions are just as important to us; that’s why we offer support any way we can—when you thrive, we all thrive. Explore your next step at Accenture Belong. Grow. Thrive. Join agreat place to work for reinventors who drive meaningful change for our clients, communities, and the world. Wo rld. Explore your next step at Accenture