AI/ML Data Engineer

Precise Software Solutions Incorporated; Washington (District of Columbia); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Health benefits

Paid Time Off

Paid parental leave

Disability insurance

Training and development

Charity donation match

Job summary

Precise Software Solutions Incorporated is looking for an AI/ML Data Engineer to design and govern the data foundation for secure AI-enabled applications in Washington, DC. You will own AI-ready datasets end-to-end, ensuring provenance, drift monitoring, and governance across FedRAMP-enabled environments.

You’ll build data pipelines, vector stores, and embedding schemas for RAG knowledge bases, while validating model quality and preparing deliverables for government data calls.

Qualifications

• BA/BS degree in CS, Engineering, Math, or related field with 5+ years of experience (or equivalent).
• 5+ years hands-on data engineering or database development; SQL and ETL/ELT pipelines needed.
• Strong Python skills and experience with pandas, Spark, and Airflow.
• Experience preparing data for Generative AI and embeddings, vector DBs, or RAG pipelines.
• Experience with data quality, lineage, metadata, and governance controls.
• Experience protecting sensitive data (PII) with masking and access controls.
• Experience with a major cloud data platform and DevOps tooling; U.S. citizenship or green card; able to work onsite in DC.

Responsibilities

• Design and maintain data ingestion, transformation, and processing pipelines for AI training and ops.
• Curate, validate, and version datasets with metadata, lineage, and logs.
• Implement data-quality checks and drift reports; maintain quality scorecards.
• Design data models, vector stores, and embedding schemas for RAG knowledge bases.
• Measure retrieval/model quality using precision/recall, MRR, NDCG, and relevance.
• Prepare data-related deliverables and documentation for governance and calls.
• Build secure data paths for AI apps with role-based access and SQL interfaces.
• Monitor pipelines, troubleshoot failures, and support FedRAMP/FIPS-compliant regions.
• Support Responsible AI by evaluating outputs for bias and reliability.
• Secure data flow from sources to prompts and logs, including risk testing.

Skills

Python

pandas

Spark

ETL/ELT pipelines

SQL

Data modeling

Airflow

RAG knowledge bases

Data governance

PII protection

Education

Bachelor’s degree in CS/Engineering/Related

Master’s degree in related field

Tools

OpenSearch

pgvector

Git

CI/CD

Job description

Precise Software Solutions Incorporated is hiring an AI/ML Data Engineer in Washington, DC for an onsite role supporting the U.S. Government. This position focuses on designing and governing the data foundation that enables secure AI-enabled applications, with end-to-end ownership of AI-ready datasets and measurable, secure AI operations.

What You’ll Do

• Design and maintain data ingestion, transformation, and processing pipelines (ETL/ELT) for AI training, evaluation, retrieval, and operations, including support for data migration and cleansing.
• Curate, validate, and version datasets while maintaining dataset inventories, metadata, lineage, provenance, and ingestion logs.
• Implement automated data-quality checks for duplication, schema changes, completeness, and freshness; maintain dataset quality scorecards and drift reports.
• Design data models, vector stores, and embedding schemas for Retrieval-Augmented Generation (RAG) knowledge bases, including re-indexing content when sources change.
• Measure retrieval and model quality against established baselines using metrics such as precision/recall, MRR, NDCG, and context relevance.
• Prepare data-related deliverables, including AI model cards, ML and AI pipeline documentation, RAG/AI pipeline evaluation reports, data dictionaries, embedding schema documentation, and responses to Government data calls.
• Build secure structured-data access for AI applications such as natural-language-to-SQL with query validation and role-based authorization, and support dashboards and operational analytics.
• Monitor data and ML pipelines, troubleshoot failures, and support root-cause analysis while keeping data in FedRAMP-authorized cloud regions using FIPS-validated encryption.
• Support Responsible AI by preparing representative evaluation datasets, testing AI outputs for bias, accuracy, and hallucination, and documenting results to align with federal AI governance requirements.
• Secure the AI data path from source datasets and embeddings to prompts and logs, including support for AI risk testing such as data poisoning.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Information Systems, or a related field and 5+ years of relevant experience; equivalent experience may substitute for the degree.
• 5+ years of hands-on data engineering or database development experience, including data modeling, SQL, and ETL/ELT pipeline development.
• Strong proficiency in Python and experience with data processing frameworks such as pandas and Spark, plus workflow orchestration tools such as Airflow.
• 1+ year preparing data for Generative AI or machine learning, including embeddings, vector databases, RAG knowledge bases, or training and evaluation datasets.
• Experience implementing data quality, lineage, metadata management, and data governance controls.
• Experience protecting sensitive data (PII), including masking, minimization, and access controls.
• Experience with a major cloud data platform (AWS, Azure, or Google Cloud), Git, and CI/CD tools.
• Must be a U.S. citizen or lawful permanent resident (green card holder).
• Must reside in the Washington, DC metropolitan area and be able to work onsite at Government offices.
• Must be able to obtain and maintain a Public Trust background investigation.

Technology Stack

• Python, pandas, Spark, Airflow, AWS, Azure, Google Cloud, Git, CI/CD
• Vector stores, vector databases, pgvector, OpenSearch
• FIPS-validated encryption, FedRAMP-authorized cloud regions
• Natural-language-to-SQL

Benefits

• Comprehensive Health Benefits (Medical, Dental and Vision)
• Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
• Retirement Plan with 4% match and discretionary match at year end
• Paid Time Off (PTO): 15 days of PTO accrued per year; 7 holidays + 3 Floating holidays; 2 Innovation days (paid training days)
• Short Term and Long-Term Disability
• Paid Parental Leave
• Paid Jury Duty leave
• Life and AD&D Insurance
• Critical Illness Insurance
• Training and Development
• Wellness Incentives & Discount programs
• Employee Referral Program
• Annual Charity Donation Match
• Awards and Recognition

Preferred Qualifications

• Master’s degree in a related field and 7+ years of data engineering experience, including support of federal agency programs.
• Experience evaluating retrieval quality and building RAG pipelines with vector stores (e.g., pgvector, OpenSearch).
• Experience with MLOps tooling, including model and dataset versioning, feature stores, or model registries.
• Generative AI, LLM security, or data certification (e.g., Databricks Generative AI Engineer, Snowflake SnowPro, AWS, Microsoft Azure, or Google Cloud).
• An active Public Trust or prior federal background investigation.