Accenture

AI Native Transformation Enterprise Consultant

Accenture$70K — $196K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 2+ years of hands-on experience building innovative applications or open-source contributions
  • 2+ years of ability to explain complex AI concepts to non-technical audiences
  • 2+ years of experience designing AI-integrated software systems
  • 4+ years of experience working in agile teams
  • 2+ years of experience with AI system observability and debugging
  • Bachelor's degree or equivalent work experience (12 years) required

Responsibilities

  • Leverage AI technologies to transform traditional business processes
  • Design state-of-the-art agentic systems to enhance legacy systems
  • Utilize AI agents for comprehensive analysis and mapping of existing systems
  • Build and scale AI-native solutions tailored for enterprise needs
  • Collaborate directly with clients to refine and improve products and experiences

Benefits

  • Medical, dental, and vision coverage
  • Life and long-term disability insurance
  • 401(k) plan with employer contributions
  • Bonus opportunities based on performance
  • Paid holidays and time off
Full Job Description
The Work

Most software developers, engineers, and architects get to build software systems. Very few get to transform how industries operate. We're combining AI technology, industry expertise, and entrepreneurial experience to fundamentally reimagine core business processes across financial services, healthcare, procurement, retail, and logistics. We partner with our clients to build better products and experiences at enterprise scale.
  • We're doing this by leveraging agentic architectures, multi-agent orchestration patterns, and composable AI systems alongside proven distributed patterns (Event Sourcing, Event-Driven Architecture, Microservices, Domain-Driven Design, CQRS) and technologies such as (Claude API, Neo4j, Qdrant, PostgreSQL, event streaming platforms, vector databases, cloud platforms) to build AI-native solutions for the enterprise.
  • Most of our work fits what we call AI Transformation Decoupling: we design and build state-of-the-art agentic systems to wrap legacy cores, establish real-time feedback loops, add new AI-native functionality, and methodically transform existing systems into composable, event-driven architectures that support human-AI collaboration at scale.
  • Before we change anything, we use AI agents to systematically understand what exists-mapping dependencies, analyzing git history, discovering hidden coupling, and identifying knowledge concentration-transforming months of manual analysis into days of comprehensive intelligence. This means transformations informed by reality, not assumptions, and changes that don't break production because we discovered the constraints first. You'll learn patterns proven in production, understand when each applies and why, and build systems that scale because they're architecturally sound-not just technically sophisticated.
  • Our team is deeply hands-on, highly technical, and prides itself on being battle-hardened, lead-from-the-front AI transformation thought leaders


Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Here's what you need
  • Minimum of 2 years of hands-on experience building interesting and innovative applications, or equivalent open-source contribution (several projects as ongoing contributor).
  • Minimum of 2 years of experience explaining complex AI concepts to a non-technical audience. If you can explain what RAG, semantic search, or multi-agent orchestration are to a layperson, you've got this.
  • Minimum of 2 years of experience designing software systems that incorporate AI components-understanding when AI is appropriate, designing around its limitations, and creating fallback mechanisms.
  • Minimum of 4 years of experience working in an agile team.
  • Minimum of 2 years of experience and understanding of AI system observability and debugging (LLM tracing, analyzing failure modes)
  • Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)


Bonus Points if you Have
  • Experience building with LLM APIs (Claude, GPT-4, etc.) and understanding prompt engineering patterns
  • Experience designing multi-agent systems with distinct roles (planning, execution, evaluation, coordination)
  • Experience designing and building MCP Server and Client including standard connection, tools and data exposure as well as specific tools
  • Experience with agentic frameworks (LangChain, LlamaIndex, or custom orchestration patterns)
  • Experience analyzing and transforming existing systems-understanding legacy architectures through systematic dependency analysis, git history mining, and architectural discovery before modification (brownfield work is most of enterprise AI)
  • Hands-on experience with vector databases and RAG architectures (Qdrant, Pinecone, ChromaDB, Weaviate)
  • Understanding of graph databases and knowledge graphs (Neo4j, Neptune) for semantic relationships and ontology modeling
  • Hands-on experience with cloud platforms (AWS, Azure, or GCP)-specifically choosing and configuring components for AI-native architectures
  • Experience with event-driven architectures and streaming technologies (Kafka, Kinesis, EventBridge, event streaming platforms) for real-time AI feedback loops
  • Experience with microservices architectures and composable system design
  • Experience with containerization and orchestration (Docker, Kubernetes, ECS)
  • Understanding of observability and monitoring for AI systems (LLM tracing, token usage, latency, cost tracking)
  • Experience with production AI operations-LLMOps, prompt versioning, model lifecycle management, or managing AI systems at scale
  • Experience with real-time communication protocols (WebSockets, Server-Sent Events, HTTP/2) for human-AI interaction patterns
  • Experience with distributed transactional data stores and their consistency models
  • Functional programming experience, particularly patterns relevant to AI systems (immutability, pure functions, composition)
  • Understanding of information retrieval, semantic search, or embedding-based similarity
  • Prior experience in traditional ML/data science (helpful but not required-we're often doing something quite different)


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 06/30/2026.

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 $70,350 to $196,000
Cleveland $59,100 to $156,800
Colorado $63,800 to $169,300
District of Columbia $68,000 to $180,300
Illinois $59,100 to $169,300
Maryland $63,800 to $169,300
Massachusetts $63,800 to $180,300
Minnesota $63,800 to $169,300
New York $66,300 to $196,000
New Jersey $68,000 to $196,000
Washington $80,200 to $180,300

About Accenture

Accenture plc is a multinational professional services company that provides services in strategy, consulting, digital, technology, and operations. The company has more than 537,000 employees serving clients in more than 120 countries. Accenture operates across five business segments: Communications, Media & Technology; Financial Services; Health & Public Service; Products; and Resources. The company is headquartered in Dublin, Ireland, and has offices worldwide.
Learn more about Accenture
Size
624,000 employees
Market Cap
$173.8 billion
Industry
Net Income
$5.2 billion
Founded
1989
5 Year Trend
+11.2%
Revenue
$44.7 billion
NASDAQ

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