Accenture

Generative AI Applications Engineer (Agents & RAG)

Accenture$103K — $203K *
Education, Government & Non-Profit
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of hands-on experience with Generative AI applications
  • Strong proficiency in Python programming language
  • Experience in LLM selection, evaluation, and prompt authoring
  • Familiarity with vector search technologies and retrieval systems
  • Understanding of security principles, especially in regulated environments
  • U.S. Citizenship required

Responsibilities

  • Design and develop mission-grade Generative AI applications
  • Implement agent frameworks and orchestration for workflows
  • Integrate platforms like AWS Bedrock and Azure OpenAI
  • Evaluate and select LLMs based on quality and performance
  • Build effective retrieval pipelines and vector searches
  • Maintain production operational rigor and incident response
  • Develop reusable platform components to enhance team productivity

Benefits

  • Comprehensive health insurance plans
  • Flexible work arrangements
  • Opportunities for professional development and training
  • Employee assistance programs
  • Paid time off and holidays
  • Retirement savings plans with employer matching
Full Job Description
Role Overview

You'll turn mission needs into secure, reliable, and scalable GenAI applications no model training required. This is a hands-on role across agentic workflows, RAG, prompt/policy design, LLM evaluation, and platform integration. You'll own the end-to-end path from use case evaluation 1 production deployment 1 operational excellence, partnering with product, security, data, and SRE to ship features safely and at scale.

What You'll Do (Day to Day)
  • Design & ship mission grade GenAI: Build agentic workflows and RAG systems tailored to mission data and environments; target low hallucination, tight p95 latency, and predictable cost.
  • Agent frameworks & orchestration: Apply patterns from LangChain/LlamaIndex/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies.
  • Platform integration (no model training): Implement with AWS Bedrock, Azure OpenAI, Google Vertex AI, Amazon Kendra, and managed services (e.g., Document AI, Gemini, Gemma).
  • LLM selection & evaluation: Compare models for quality, safety, latency, cost; author/test prompts & policies; deploy with observability and safe rollback/fallback.
  • RAG done right: Build retrieval pipelines & vector search (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise.
  • Production rigor: Instrument metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails.
  • SRE & FinOps for AI: Define SLIs/SLOs (quality/latency/safety/cost), run on call and postmortems, reduce MTTR; meter usage and optimize token/spend.
  • Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off projects.
  • Operate in real world constraints: Deliver into hybrid, restricted, or air gapped environments with Zero Trust principles and audit ready controls.


You'll Thrive Here If you have
  • End-to-end ownership of production systems: integration 1 deployment 1 observability 1 incident response.
  • Hands-on experience with LLMs, transformer based apps, and RAG in production.
  • Strong Python
  • Experience with vector search and retrieval (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma) and grounding AI in enterprise/mission data.
  • U.S. Citizenship


Nice to Have
  • Integration with leading cloud AI services or on prem inference stacks
  • Background in LLM evaluation, prompt authoring/testing, A/B experimentation, and LLM Ops.
  • Responsible AI expertise (privacy, security, bias, transparency, human in the loop) and data governance.
  • Experience implementing tool using agents for API integration and external data access.
  • Containerization & orchestration (Docker, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell).
  • Prior work in regulated/secure environments (e.g., ATO, STIGs, Zero Trust) with fast shipping.
  • Familiarity with NVIDIA AI Foundations, OpenAI ChatGPT, and AI assisted dev tools (Cursor, Windsurf, Claude).
  • Contributions to internal frameworks or opensource; mentorship of engineers.
  • Clear communication with engineers, PMs, and security/compliance stakeholders.


As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.

The pay range for the states of California, Colorado, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland is:

$103,200-$203,400 USD

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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