Enterprise AI Transformation Consultant
$70.35k - $196kAccenture Global
We Are Accenture is recognized as a global leader in AI and cloud transformation, helping businesses across industries design, build, and operationalize AI at enterprise scale. Technology Strategy & Transformation (TS&T) - Digital Foundations builds innovative AI solutions that turn strategy into production. We Advise, Design, Build and operationalize AI solutions to deliver tangible, real results - on programs that affect how entire industries operate. Our work spans agentic AI architecture, composable and event-driven platforms, AI-assisted engineering, and the operating models and business cases that make AI adoption durable. You Are A strong software engineer with genuine curiosity about AI and the drive to build production systems on real enterprise programs. Technical depth is your foundation; you want to apply it to complex enterprise problems and grow toward senior technical and advisory roles. The Work AI is reshaping what enterprises can build, how fast they can move, and where competitive advantage comes from. As a Consultant, you are a hands-on builder and technical contributor on AI transformation programs:
- Build agentic systems : Write production code: multi-agent systems (planning, execution, evaluation, and coordination roles), LLM integrations with LLM APIs (Claude/Anthropic, GPT-4) and prompt engineering, agentic frameworks (LangChain, LlamaIndex, or equivalent), RAG pipelines, vector search or embedding-based retrieval, MCP Server/Client, composable AI components, and the software engineering that makes them reliable at scale. Work with vector databases (Qdrant, Pinecone, ChromaDB, Weaviate) and graph databases and knowledge graphs (Neo4j, Neptune). This is the core of the role.
- Engineer with AI coding agents: Use AI coding agents (Claude Code, GitHub Copilot, Cursor) daily, alongside testing, version control, and CI/CD, to ship production code.
- Contribute to solution architecture: Work alongside Architects to translate architecture decisions into working systems. Your implementation experience directly informs architecture quality. Apply microservices, event-driven design (including streaming on Kafka, Kinesis, or EventBridge), API-led integration, and containerization and orchestration (Docker, Kubernetes). Understand how data moves between systems, basic transformation patterns, and what AI systems need from data. Know how AWS, Azure, and GCP services are used in production, and where integration and complexity live across enterprise platforms (ERP, CRM, data platforms).
- Test and observe AI quality: Contribute to AI evaluation (quality assurance, risk assessment, and compliance for enterprise AI deployments) and AI observability (LLM tracing, failure mode analysis, LLMOps, prompt versioning).
- Deliver your workstream: Manage your own tasks within a delivery workstream: plan the work, meet commitments, flag blockers early, and understand how your work fits into the wider program and what depends on it. Communicate progress and blockers clearly to senior practitioners and team leads, and take ownership without waiting to be told what to do next.
- Develop client-facing skills: Build technical credibility with client engineering and architecture teams through delivery. Document technical decisions, write clear specifications, break technical requirements into discrete tasks, present your work to senior practitioners, and act on feedback. Build awareness of how the client's vertical (financial services, healthcare, retail, logistics, or public sector) shapes the work.
- Learn and apply practice patterns: Engage with established patterns for agentic AI, document what you learn, and contribute to reusable assets. Explore developments in agentic AI, test new approaches, and bring learnings into delivery work.
- Minimum of 3 years of experience in software engineering or technology consulting.
- Minimum of 3 years of hands-on software development experience with production deployments, including testing, version control, and CI/CD.
- Minimum of 1 year of experience building with LLM APIs or AI/ML components in production contexts.
- Minimum of 1 year of experience using AI coding agents (for example Claude Code, GitHub Copilot, or Cursor) in software development workflows.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)
- Industry experience in at least one vertical (financial services, healthcare, retail, logistics, or public sector)
- AI evaluation: quality assurance, risk assessment, and compliance for enterprise AI deployments
- AI observability: LLM tracing, failure mode analysis, LLMOps, prompt versioning
- Cloud certification (AWS, Azure, GCP) or AI/ML certification (AWS ML Specialty, GCP Professional ML Engineer, Azure AI Engineer)
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$105.6k - $199.48k
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$70.35k - $205.8k
...Accenture helps the world's leading enterprises reinvent by building their... ...and unleashing the power of AI to create value at speed for... ...: Accenture is seeking a Consultant to drive hands-on execution... ...Transportation Management transformation programs within our Supply Chain...Full timeLive inWork at officeLocal area- ...AWS Applied AI Solutions is hiring for senior engineering leadership roles to own and ship finished AI solutions at enterprise scale in the United States. You will architect end-to-end systems where thousands of autonomous agents operate in production, collaborating with...
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$153k - $180k
...do. Expectations are high, and so are the rewards. The Corporate Engineering team is building and scaling the next generation of enterprise AI infrastructure at Robinhood. Our mission is to make AI capabilities reliable, secure, and accessible across the company,...Work at officeFlexible hoursShift work3 days per week- Robinhood is seeking a Senior AI Operations Engineer in Enterprise Tech to design, deploy, and operate our enterprise AI infrastructure across Bellevue, WA; NYC; and Menlo Park. The role emphasizes internal tooling, observability, and robust LLM integrations to support...
$70.35k - $205.8k
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