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Benefits & Perks
•Healthcare
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•Disability Insurance
•401(k)
•Paid Leave
•Professional Development
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Required Skills
Data architecture
Data engineering
Python
SQL
AI/ML
Knowledge management
Semantic search
Vector databases
ETL
Artificial Intelligence Engineer:
The Opportunity:
Design and build robust knowledge frameworks, enabling AI systems to dynamically interact with structured and unstructured public health data, facilitating real-time insights and decision-making support. Leverage knowledge of the design and implementation of base architectures, data modeling for AI agents, Memory and State Management, and construction of RAG Pipeline Design to facilitate multi-modal data integration partnering closely with data engineers on data pipeline coordination. Support performance optimization of retrieval processes for public health use cases and define rigorous data quality and curation standards. Collaborate with AI teams and maintain thorough documentation of data architecture. Ensure compliance with data privacy standards, anonymization protocols, and ethical guidelines critical to public health data management.
You Have:
-
4 years of experience in data architecture or engineering, including AI, ML or knowledge-based systems
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Experience in knowledge management, semantic search, and public health information retrieval
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Experience with vector databases such as Azure AI Search, PostgreSQL PgVector, Pinecone, Weaviate, or FAISS, and graph databases such as Neo4j, or AWS Neptune
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Experience in ETL processes, data integration, and scripting, including Python, SQL, or API-driven architectures
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Knowledge of enterprise search technologies, including Elasticsearch or Solr, and dense vector search methodologies
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Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
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Bachelor’s degree
Nice If You Have:
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Experience in designing knowledge graphs, ontologies, and semantic frameworks such as RDF, OWL, or Neo4j
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Experience in data governance, curation processes, and quality assurance practices within regulated health environments
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Experience with analytics to abstract complex public health data into structured, actionable models
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Experience in data-centric AI or ML projects within healthcare, biomedical, or public health sectors
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Experience in designing APIs, microservices architecture such as FastAPI or Flask, and caching mechanisms such as Redis
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Knowledge of cloud-based AI data platforms such as AWS Kendra, AWS Bedrock, Azure Cognitive Search, or GCP Vertex AI
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Knowledge of data ethics, privacy standards, and security protocols
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Knowledge of NLP methods and libraries such as spa Cy, NLTK, or Hugging Face Transformers
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Ability to adopt and implement emerging AI technologies such as Llama Index or advanced memory architectures
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Possession of superior communication skills, to facilitate collaboration between technical teams, public health experts, and stakeholders
Vetting:
Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.
Compensation
At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen’s benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.
Salary at Booz Allen is determined by various factors, including but not limited to location, the individual’s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.
Identity Statement
As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Work Model
Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely.
- If this position is listed as remote or hybrid, you’ll periodically work from a Booz Allen or client site facility.
- If this position is listed as onsite, you’ll work with colleagues and clients in person, as needed for the specific role.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.
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About Booz Allen Hamilton

Booz Allen Hamilton
PublicSpecializing in digital transformation and artificial intelligence.
10,001+
Employees
McLean
Headquarters
Reviews
3.5
5 reviews
Work Life Balance
2.5
Compensation
3.0
Culture
2.8
Career
2.5
Management
2.0
35%
Recommend to a Friend
Pros
Great reputation in federal sector
Hybrid work options available
Established teams and processes
Cons
Poor hiring and recruitment process
Job security concerns with contract-based work
Work-life balance issues
Salary Ranges
34 data points
Junior/L3
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
Junior/L3 · Data Engineer
1 reports
$149,500
total / year
Base
$115,000
Stock
-
Bonus
-
$149,500
$149,500
Interview Experience
7 interviews
Difficulty
2.7
/ 5
Duration
21-35 weeks
Offer Rate
43%
Experience
Positive 29%
Neutral 28%
Negative 43%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Hiring Manager Interview
5
Team Interview
6
Offer
Common Questions
Technical Knowledge
Behavioral/STAR
Past Experience
System Design
Culture Fit
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