AI Integration Analyst

Accenture Federal Services•Washington, DC

9d•$86,400 - $176,200•Hybrid

About The Position

At Accenture Federal Services, our purpose is to make the US federal government stronger and safer, and to improve people's lives. We are a technology company within global Accenture, with over 13,000 employees dedicated to leveraging technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. We are recognized as a Glassdoor Top 100 Best Place to Work, offering a collaborative and supportive community where employees can grow, learn, and thrive through hands-on experience, certifications, and industry training. Join us to drive positive, lasting change that advances missions and the government forward. As an AI Integration Analyst, you will be instrumental in building and delivering AI-enabled solutions that address mission needs and enhance user experience. You will collaborate closely with product owners, engineers, data/AI teams, and security/compliance partners to translate requirements into functional features, integrate AI components into existing systems, and ensure solutions are reliable, safe, and adhere to organizational standards. This is a growth-oriented role for individuals who are hands-on, curious, and eager to expand their expertise in applied AI development and integration.

Requirements

US Citizen, no dual citizenship (Public Trust eligible)
Experience integrating or supporting AI- or data-powered features within software products or internal tools.
Familiarity with backlog management, writing user stories, defining KPIs, and contributing to iterative release cycles.
Practical understanding of privacy/security concepts and how to apply guardrails within product workflows.
Comfortable working with engineering, data/AI, and security/compliance partners in cross-functional settings.
Ability to understand and discuss topics such as LLM orchestration, RAG patterns, prompt design, and data pipelines at a technical-collaborator level.
Demonstrated success contributing to solutions that reached production and delivered measurable impact.

Nice To Haves

Experience working in regulated or secure environments and familiarity with audit requirements or Zero Trust principles.
Familiarity with cloud and data platforms such as Azure, AWS, GCP, Databricks, Snowflake, Palantir, vector search, or metadata/catalog tools.
Exposure to LLM evaluation frameworks, prompt lifecycle practices, or agent-based workflows.
Experience developing internal documentation, reusable templates, or lightweight standards.

Responsibilities

Translate stakeholder needs into clear technical requirements, user stories, and acceptance criteria.
Collaborate with engineering and data teams to integrate AI components (LLMs, RAG, agents, analytics) into applications and workflows.
Support MVPs, pilots, and iterative releases; help run experiments, evaluate results, and incorporate feedback.
Assist in implementing guardrails such as filtering, citation pipelines, prompt versioning, and basic human-in-the-loop flows.
Contribute to evaluation processes by helping define and measure quality, safety, latency, and reliability metrics.
Ensure integrations comply with security, privacy, and policy requirements, document controls for audit readiness.
Troubleshoot issues, participate in post-incident reviews, and help improve system reliability.
Create templates, checklists, and lightweight playbooks that scale across teams.
Work within hybrid, restricted, or on-prem environments and understand constraints that impact architecture and deployment.
Communicate progress clearly to project leads and contribute to decision-making with data-backed input.