Context Layer Engineer

Context Layer Engineer

The Opportunity:

As a Context Layer Engineer, you’re excited by the challenge of designing systems that can interpret, enrich, and operationalize context across complex data and AI ecosystems. In a growing business, disparate data systems require sophisticated contextualization to create meaningful, reliable, and mission‑ready outputs. As a Context Layer Engineer at Booz Allen, you will help architect and optimize the contextual intelligence layer that powers advanced analytics, reporting pipelines, machine learning models, and enterprise AI solutions.

On our team, you’ll leverage deep expertise in contextual data engineering to create real-world impact. You’ll collaborate closely with clients to understand their mission needs and translate those into context models, ontologies, enrichment logic, and integration patterns. You’ll guide teammates and lead the development of systems and algorithms that unify disparate data sources, resolve entities, incorporate domain knowledge, and deliver structured context to downstream applications. You’ll use the right combination of tools and frameworks to build resilient context pipelines that enhance model performance, enable decision‑quality insights, and support intelligent automation.

Ultimately, you’ll engineer the critical connective tissue between raw data and operational AI, enabling your clients to understand what their data means, how it should be interpreted, and how it can be used. Due to the nature of work performed within this facility, U.S. citizenship is required.

Join us. The world can’t wait.  

You Have:   

• 5+ years of experience with data exploration, data cleaning, data analysis, data visualization, or data mining 
• 5+ years of experience analyzing structured and unstructured data sources  
• Experience in data manipulation leveraging R, Python, or SQL or NoSQL 
• Experience supporting operational AI, quantitative analyses, and visualization of targeted data sources  
• Experience leading the development of solutions to complex programs 
• Experience with natural language processing, text mining, or machine learning techniques 
• Bachelor’s degree 

Nice If You Have:   

• Experience with distributed data or computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL  
• Experience with semantic layer tools such as Cube, dbt Semantic Layer, or Databricks Unity Catalog Semantics

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 hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. 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.

Candidate AI Usage Policy

AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided.

Work Model
Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings.

• Remote: If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility.

• Hybrid: If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility.

• Onsite: If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the 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.