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enterprise data and ai solutions scientist Jobs in Washington

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senior big data developer

data engineer

VERSA Integrated Solutions

Position: Data EngineerDepartment: Federal ProgramsLocation: Washington, DC Metro Area (Hybrid/Onsite based on customer requirements)Employment Type: Full-TimeSalary: Commensurate with ExperienceAbout VERSA Integrated SolutionsVERSA Integrated Solutions delivers innovative Cloud, Data, Artificial Intelligence, Cybersecurity, and Enterprise IT solutions to Federal Government agencies. We help agencies modernize mission-critical systems by implementing secure, scalable, cloud-native technologies that enable advanced analytics, operational excellence, and data-driven decision making.Position SummaryVERSA Integrated Solutions is seeking a highly motivated Data Engineer to design, build, optimize, and maintain enterprise data platforms supporting Federal Government customers. The Data Engineer develops robust ETL/ELT pipelines, cloud-based data integration solutions, and enterprise data repositories that support business intelligence, artificial intelligence, reporting, and operational analytics.The successful candidate will collaborate closely with Data Architects, AI/ML Engineers, Database Administrators, Software Developers, Cloud Engineers, and Business Analysts to ensure high-quality, secure, and scalable data solutions.Position ObjectivesThe Data Engineer will:<ul><li>Design enterprise data pipelines.&bull; Integrate structured and unstructured data sources.&bull; Support cloud data modernization initiatives.&bull; Improve enterprise data quality.&bull; Enable analytics and AI initiatives.&bull; Automate data processing workflows.</li></ul>Major Duties &amp; ResponsibilitiesData Pipeline Development<ul><li>Design, develop, and maintain scalable ETL/ELT pipelines.&bull; Integrate internal and external data sources.&bull; Automate ingestion, transformation, and validation processes.&bull; Optimize data movement across enterprise platforms.&bull; Monitor pipeline performance and reliability.</li></ul>Cloud Data EngineeringSupport enterprise cloud platforms including:<ul><li>Azure Data Factory&bull; Azure Synapse Analytics&bull; Azure Data Lake&bull; Microsoft Fabric&bull; AWS Glue&bull; AWS Redshift&bull; Databricks</li></ul>Develop cloud-native data integration solutions supporting modernization initiatives.Data Integration<ul><li>Develop APIs supporting enterprise integrations.&bull; Process structured, semi-structured, and unstructured data.&bull; Build real-time and batch processing solutions.&bull; Support streaming technologies such as Apache Kafka and Azure Event Hub.</li></ul>Data Quality<ul><li>Validate incoming datasets.&bull; Develop automated quality checks.&bull; Monitor completeness and accuracy.&bull; Resolve data anomalies.&bull; Implement data lineage and audit capabilities.</li></ul>Analytics SupportProvide data services supporting:<ul><li>Power BI&bull; Tableau&bull; AI/ML models&bull; Executive dashboards&bull; Predictive analytics&bull; Operational reporting</li></ul>DevSecOpsCollaborate with engineering teams to:<ul><li>Automate deployments&bull; Implement Infrastructure as Code&bull; Support CI/CD pipelines&bull; Improve monitoring and observability&bull; Secure enterprise data environments</li></ul>Required Technical SkillsLanguages<ul><li>Python&bull; SQL&bull; Spark&bull; PySpark&bull; PowerShell</li></ul>Cloud<ul><li>Azure&bull; Azure Data Factory&bull; Azure Synapse&bull; Azure SQL&bull; Azure Storage&bull; Microsoft Fabric</li></ul>Databases<ul><li>SQL Server&bull; PostgreSQL&bull; Oracle&bull; Snowflake&bull; Databricks</li></ul>Tools<ul><li>Git&bull; GitHub&bull; Azure DevOps&bull; Terraform&bull; Docker&bull; Kubernetes</li></ul>Preferred Skills<ul><li>Apache Kafka&bull; Azure Event Hub&bull; REST APIs&bull; JSON/XML&bull; Delta Lake&bull; Data Lakehouse Architecture&bull; AI data preparation&bull; MLOps</li></ul>EducationBachelor's degree in Computer Science, Information Systems, Engineering, Data Science, Mathematics, or a related discipline.Experience LevelsJunior (0&ndash;4 Years)<ul><li>SQL development&bull; Python programming&bull; ETL fundamentals&bull; Database experience</li></ul>Intermediate (5&ndash;9 Years)<ul><li>Cloud data engineering&bull; Azure or AWS experience&bull; Production ETL development&bull; API integration</li></ul>Senior (10&ndash;14 Years)<ul><li>Enterprise cloud modernization&bull; Data platform leadership&bull; Performance optimization&bull; Mentoring junior engineers</li></ul>SME (15+ Years)<ul><li>Enterprise Data Engineering strategy&bull; Federal modernization leadership&bull; AI-enabled data platforms&bull; Large-scale cloud migration</li></ul>Preferred Certifications<ul><li>Microsoft Certified: Azure Data Engineer Associate&bull; Databricks Certified Data Engineer&bull; AWS Certified Data Engineer&bull; SnowPro Core&bull; ITIL&reg; Foundation</li></ul>Desired Federal ExperienceExperience supporting NIH, CMS, Census Bureau, Commerce, DHS, DOD, or other Federal agencies is highly desirable.Security ClearanceAbility to obtain and maintain a Public Trust or higher clearance, depending on customer requirements.Why Join VERSA?Join a team building modern data platforms that enable Federal agencies to leverage artificial intelligence, cloud computing, and enterprise analytics to accomplish mission objectives.Equal Employment OpportunityVERSA Integrated Solutions is an Equal Opportunity Employer committed to diversity, inclusion, and equal opportunity for all qualified applicants.Pay: $120,000.00 - $150,000.00 per yearBenefits:<ul><li>401(k) matching</li><li>Health insurance</li><li>Life insurance</li><li>Paid time off</li><li>Vision insurance</li></ul>Work Location: Hybrid remote in Washington, DC 20591

Data Engineer

Fustis LLC

<div>Job Title:
Senior Big Data Developer
Location:
Washington, DC - Hybrid - Locals
Duration:
12 Months
Work Authorisation:
USC, GC, GC-EAD and H4-EAD
Pay Rate:
90-100/hr. on C2C
Mode of Interview:
Virtual 
<h2 class="jobSectionHeader"> 
Position Overview</h2>
The Data Architecture, Technology, and Analytics (DATA) team within the Federal Reserve Board&rsquo;s Division of Research &amp; Statistics (R&amp;S) is responsible for transforming how enterprise data is ingested, organized, analyzed, and visualized to support economic research and policy decision-making.
We are seeking a highly skilled Data Architect / Data Engineer to design, develop, and optimize modern data architectures, enterprise data platforms, and scalable data pipelines. This individual will play a critical role in supporting economists, researchers, analysts, and technical teams by ensuring efficient, reliable, and scalable access to data across the organization.
The ideal candidate is a hands-on data professional with deep expertise in data modeling, database architecture, ETL/ELT development, cloud platforms, and enterprise data management. This role requires strong analytical capabilities, excellent communication skills, and a passion for building data solutions that enable advanced research and business intelligence.
Key Responsibilities
Design, develop, and maintain enterprise-scale data architectures and data platforms. Build and optimize scalable ETL/ELT pipelines for ingestion, transformation, and delivery of structured and unstructured data. Develop conceptual, logical, and physical data models aligned with enterprise architecture standards. Architect and manage relational databases, data warehouses, data lakes, and modern data ecosystems. Support migration of data workflows and pipelines between on-premises and cloud environments. Implement workflow orchestration and automation using tools such as Airflow, Prefect, Dagster, or AWS Step Functions. Perform data integration across multiple internal and external data sources. Design and implement Change Data Capture (CDC) solutions for enterprise data warehousing initiatives. Optimize database performance, scalability, reliability, and data processing workloads. Collaborate with economists, researchers, analysts, and technical stakeholders to understand business requirements and deliver effective data solutions. Conduct root cause analysis of data issues and identify opportunities for process improvement and automation. Implement and maintain CI/CD pipelines and DataOps practices for data engineering projects. Support machine learning and advanced analytics initiatives through efficient data infrastructure and model deployment frameworks. Ensure data governance, security, quality, and compliance standards are followed across all solutions. Document architecture designs, technical specifications, and operational procedures. Required Qualifications
Education
Bachelor&rsquo;s Degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical field. Master&rsquo;s Degree or other advanced degree is preferred. Experience
Minimum 7+ years of experience in Data Engineering, Data Architecture, Database Engineering, or related fields. Proven experience designing and implementing enterprise data platforms and large-scale data solutions. Required Technical Skills
Data Engineering &amp; Architecture
Strong expertise in data architecture, data modeling, and enterprise information architecture. Experience designing conceptual, logical, and physical data models. Extensive experience building and maintaining scalable data pipelines and processing frameworks. Experience implementing enterprise data warehouses, data lakes, and modern analytics platforms. Strong understanding of Change Data Capture (CDC) methodologies. Databases
Advanced SQL expertise. Hands-on experience with: PostgreSQL Microsoft SQL Server MySQL Experience with database administration, optimization, and performance tuning. Programming &amp; Scripting
Advanced proficiency in: Python R Strong scripting and automation experience. Experience with additional programming languages such as: Java Scala JavaScript Perl ETL/ELT &amp; Workflow Automation
Experience designing and automating ETL/ELT processes. Hands-on experience with workflow orchestration tools such as: Apache Airflow Prefect Dagster AWS Step Functions Cloud &amp; Modern Data Platforms
Experience working with: AWS Microsoft Azure Snowflake Experience migrating applications and data pipelines between on-premises and cloud environments. DevOps &amp; DataOps
Experience implementing and maintaining: CI/CD pipelines DataOps frameworks Experience with Git-based source control platforms: GitHub GitLab Big Data &amp; Analytics
Experience with: Distributed computing frameworks Large-scale data processing systems High-volume data workloads Experience processing structured and unstructured datasets. Linux &amp; Infrastructure
Strong development and deployment experience in Linux environments. Preferred Qualifications
Experience working with economic, financial, or regulatory datasets. Experience supporting research organizations or data-driven policy environments. Understanding of time-series data modeling, forecasting, and statistical analysis techniques. Experience with NoSQL technologies and Graph Databases. Experience developing, deploying, and maintaining Machine Learning models. Knowledge of enterprise data governance and metadata management frameworks. Experience supporting advanced analytics and AI-driven data initiatives. Soft Skills
Excellent verbal and written communication skills. Strong stakeholder management and customer service mindset. Exceptional analytical and problem-solving abilities. Ability to work independently and manage multiple priorities simultaneously. Strong troubleshooting and root-cause analysis skills. Detail-oriented with a focus on quality and continuous improvement.</div>

Senior Big Data Developer

Databricks

<div>CSQ227R88
PLEASE NOTE:
 
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply.
As a Sr. Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data &amp; AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.
This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.
The impact you will have:
<ul><li>Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration</li>
<li>Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer</li>
<li>Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.</li>
<li>Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.</li>
<li>Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.</li>
<li>Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.</li>
<li>Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.</li>
<li>Reusable Assets &amp; Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.</li>
</ul>What we look for:
<ul><li>6+ years experience in data engineering, data platforms &amp; analytics, or software engineering</li>
<li>Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks</li>
<li>Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one</li>
<li>Deep experience with distributed computing with Apache Spark&trade; and knowledge of Spark runtime internals</li>
<li>Familiarity with CI/CD for production deployments</li>
<li>Working knowledge of MLOps, ML/AI models and AI APIs</li>
<li>Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.</li>
<li>Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.</li>
<li>Documentation and white-boarding skills.</li>
<li>Experience working with enterprise clients and managing conflicts across a broad stakeholder range</li>
<li>Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.</li>
<li>Travel to customers 20% of the time</li>
<li>Databricks Certification</li>
</ul><div><div><div>Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. 
 
</div><div>Zone 1 Pay Range</div>
<div>$180,656&mdash;$248,360 USD
</div></div><div><div>Zone 2 Pay Range</div>
<div>$180,656&mdash;$248,360 USD
</div></div><div><div>Zone 3 Pay Range</div>
<div>$180,656&mdash;$248,360 USD
</div></div><div><div>Zone 4 Pay Range</div>
<div>$180,656&mdash;$248,360 USD
</div></div></div><div>About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide &mdash; including Comcast, Cond&eacute; Nast, Grammarly, and over 50% of the Fortune 500 &mdash; rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark&trade;, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
 
 
Benefits
 
 
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. 
 
 
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</div></div>

Sr. Forward Deployed Engineer (FDE) - Public Sector

National Capitol Contracting (NCC)

<div><div>Position Summary</div><div></div><div> 
This position requires an Active Secret Clearance</div><div></div><div> 
National Capitol Contracting is seeking motivated, skilled, and innovative Foundry Developer II with experience in Foundry, Qlik, Databricks, Power BI, and Python. Our work directly contributes to strengthening the Navy&rsquo;s digital and operational capabilities, and successful candidates will benefit from substantial training, mentorship, and advancement opportunities. Successful candidates will be comfortable working with enterprise-scale systems, collaborating with senior Navy and appointed leadership, and developing tools and processes for a wide range of stakeholders. 
 
NAVSEA&mdash;one of the Navy&rsquo;s six procurement commands and the organization responsible for both industrial operations and digital modernization&mdash;has partnered with National Capitol Contracting (NCC) on a congressionally funded data analytics initiative: the Naval Digital Logistics Acceleration (NDLA) program. 
 
For experienced data professionals, this is a rare opportunity to have a measurable impact on national defense, collaborate across complex organizations, and deliver solutions that will shape a more resilient, data‑driven Navy of the future.</div> 
 Essential Duties and Responsibilities<div><ul><li>
Design future-state, modern data architecture, pipelining, and analysis for transformation at the enterprise level using advanced cloud architectural principles</li><li>
Work with cutting-edge DevOps technologies and develop advanced analytics products</li><li>
Apply data pipelining and statistical programming tools to enterprise data to advance and enable key mission outcomes</li><li>
Build and optimize data pipelines and transform using Python within Foundry</li><li>
Integrate with external systems and APIs and manage data connections</li><li>
Implement automated testing</li><li>
Collaborate with stakeholders to define requirements and translate them into technical designs</li><li>
Troubleshoot, optimize, and monitor performance and data quality</li><li>
Lead code reviews; document solutions and follow best practices</li><li>
Other duties as assigned</li></ul></div><div></div><div> 
Minimum Requirements</div><div><ul><li>
Active Secret Clearance required</li><li>
9+ years of data engineering experience, software development, or analytics engineering</li><li>
Demonstrated hands-on experience with Palantir Foundry (pipelines/transforms, data modeling/ontology concepts)</li><li>
Experience with data extraction and manipulation</li><li>
Proficiency in Python and SQL</li><li>
Proven experience building data pipelines and data models</li></ul></div><div></div><div> 
Educational Requirements</div><div><ul><li>
Bachelor&rsquo;s degree in computer science, engineering, or related field</li></ul></div> 
Compensation:
$170,000-$180,000
The compensation range listed for this position is provided as a good-faith estimate of what the company intends to offer for this role. Actual compensation may vary based on factors such as job responsibilities, education, experience, skills, internal equity, budget, market data, and relevant laws.<div> 
NCC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status, political affiliation, genetic information, or any other legally protected status or characteristic. E-Verify Employer. VEVRAA Federal Contractor.</div><div></div><div> 
NCC provides reasonable accommodations to qualified individuals with disabilities. If you are an applicant that requires a reasonable accommodation, please email us at recruiting@nccsite.com. Please reference the position in your email.</div></div>

Foundry Developer II - Sr.

SAIC

<div>Job ID: 2613789
Location: Washington, DC, US
Date Posted: 2026-06-17
Category: Information Technology
Subcategory: Data Scientist
Schedule: Full-Time
Shift: Day Job
Travel: No
Minimum Clearance Required: Secret
Clearance Level Must Be Able to Obtain: None
Potential for Remote Work: ORA_HYBRID 
Description
We are seeking an Enterprise Data and AI Solutions Scientist to join our Hyperautomation team. This role is designed for an analytically curious and technically versatile &ldquo;data hunter&rdquo; who thrives when the required data source, system, field, or solution has not yet been identified.
The successful candidate will lead investigative data-discovery efforts across enterprise platforms, determine where relevant information resides, evaluate its reliability, correlate records across disparate systems, and translate findings into repeatable analytics, AI-enabled data-enrichment capabilities, and automated workflows.
This position goes beyond querying known datasets or producing predefined reports. It requires someone who can take an ambiguous business objective, investigate multiple enterprise systems, identify relationships among incomplete or conflicting datasets, and develop an evidence-based approach to solving the problem. This individual will bridge the gap between raw enterprise data, intelligent data enrichment, and automation.
What You Will Bring to the Team
You are more than a reporting specialist or traditional data scientist. You are comfortable beginning with an unanswered question, navigating unfamiliar enterprise systems, testing
This role is hybrid and reports onsite in Washington, DC at least 1 day a week and as required for meetings, testing or other gov activities as directed by their lead.
Key Responsibilities:<ul><li>
Investigative Data Discovery: Lead data-hunting and investigative analytics efforts in support of complex business, operational, security, and hyperautomation use cases.</li><li>
Platform Exploration: Investigate enterprise platforms, particularly Splunk and ServiceNow, to identify relevant indexes, sourcetypes, tables, fields, APIs, relationships, and authoritative data sources.</li><li>
Data Correlation and Reconciliation: Identify correlation keys across disparate systems, including configuration-management, endpoint, identity, asset, and operational data. Develop methods for reconciling incomplete, inconsistent, duplicated, or conflicting records.</li><li>
Advanced Querying and Scripting: Develop and optimize searches, queries, scripts, and analytical workflows using SPL, SQL, Python, REST APIs, and related data-retrieval technologies.</li><li>
AI-Driven Data Enrichment: Use approved AI and Generative AI capabilities, including prompt-based APIs, to normalize data, extract attributes, and generate missing data points from available record-level context. Examples may include using known IT asset manufacturers and models to determine or infer lifecycle attributes such as End of Life or End of Support.</li><li>
AI Output Validation: Evaluate AI-generated attributes for accuracy, consistency, and business usability. Clearly distinguish authoritative source data from inferred or generated information and document supporting evidence, confidence, and known limitations.</li><li>
Automation Integration: Partner with RPA, workflow, and data-engineering teams to convert successful analytical discoveries and enrichment processes into repeatable, governed, and sustainable enterprise capabilities.</li><li>
Solution Design: Help determine whether a use case is best addressed through data engineering, API integration, business-process automation, robotic process automation, AI-enabled enrichment, or a hybrid approach.</li><li>
Prototyping and Communication: Develop prototypes, proofs of concept, dashboards, and visualizations. Communicate findings, data limitations, technical risks, and recommendations to both technical teams and senior leadership.</li></ul>
Core Competencies:<ul><li>
Investigative Curiosity: A persistent drive to explore unfamiliar systems and data structures until a defensible answer or path forward is identified.</li><li>
Systems Thinking: The ability to understand how data flows across applications, infrastructure, identity systems, assets, and business processes.</li><li>
Evidence-Based Discipline: A rigorous approach to validating conclusions, documenting data lineage, and distinguishing authoritative, derived, and AI-generated information.</li><li>
Solution Orientation: The ability to turn one-time discoveries into reusable, scalable, and supportable enterprise capabilities.</li><li>
Consultative Communication: The ability to translate complex data findings into clear, actionable recommendations for technical and business stakeholders.</li></ul>
Illustrative Use Cases:<ul><li>
Correlating security, endpoint, identity, asset, and service-management data across Splunk, ServiceNow, and other platforms to identify vulnerable, unsupported, or untracked enterprise assets.</li><li>
Sending known asset attributes, such as manufacturer, model, product family, and software version, to an approved AI service to generate missing lifecycle information, including estimated End-of-Life and End-of-Support dates.</li><li>
Using AI to normalize inconsistent manufacturer names, product models, application titles, organizational values, and other records that cannot be reliably standardized through static rules alone.</li><li>
Validating AI-generated data against available evidence, documenting the basis for each determination, and flagging low-confidence or conflicting results for human review.</li><li>
Mapping a manual data-gathering and reconciliation process and redesigning it as an automated pipeline using Databricks, APIs, ServiceNow, Splunk, Power Automate, or RPA technologies.</li></ul>
Qualifications
Required Education &amp; Experience:<ul><li>
Bachelor&rsquo;s degree in Data Science, Computer Science, Information Systems, Statistics, Engineering, or a related technical discipline and at least 2-5 years of relevant professional experience. Equivalent practical experience may be considered in lieu of a degree.</li><li>
Demonstrated experience conducting data discovery or investigative analytics when the required data sources, fields, or technical approach were not predefined.</li><li>
Hands-on Splunk experience, including SPL development, index and sourcetype discovery, field analysis, lookups, joins, and cross-source data correlation.</li><li>
Hands-on experience navigating and querying ServiceNow data structures, including CMDB, asset, operational, or related enterprise tables and APIs.</li><li>
Strong proficiency in SQL and Python for data retrieval, manipulation, integration, and analysis.</li><li>
Experience working with REST APIs, JSON, and structured or semi-structured data.</li><li>
Practical experience using AI, Generative AI, or prompt-based services to extract, classify, normalize, infer, or enrich enterprise data.</li><li>
Experience evaluating and validating generated or inferred data before incorporating it into analytics, reporting, or operational processes.</li><li>
Ability to work independently in ambiguous environments, formulate and test hypotheses, and adapt based on emerging findings.</li><li>
Strong analytical, problem-solving, documentation, and technical communication skills.</li></ul>
Required Clearance:<ul><li>
US Citizenship.</li><li>
Active Secret Clearance.</li></ul>
Preferred Qualifications:<ul><li>
Experience with Databricks, Apache Spark, Delta Lake, or cloud-based lakehouse architectures.</li><li>
Experience integrating with AI or large language model services through APIs, including prompt design, structured outputs, response evaluation, and exception handling.</li><li>
Experience developing or supporting workflows using Microsoft Power Automate or UiPath.</li><li>
Experience operationalizing AI-generated or AI-enriched data through automated pipelines, dashboards, workflow tools, or human-in-the-loop review processes.</li><li>
Familiarity with Retrieval-Augmented Generation, semantic matching, embedding models, vector databases, entity resolution, or related information-retrieval techniques.</li><li>
Experience working in federal government, regulated-industry, cybersecurity, IT asset-management, or large-scale enterprise environments.</li></ul>
Target salary range: $80,001 - $120,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.</div>

Enterprise Data and AI Solutions Scientist

Position: AI/ML EngineerLocation: Washington, DC Metro Area (Hybrid/Onsite based on customer requirements)Employment Type: Full-TimeSalary: Commensurate with ExperienceAbout VERSA Integrated SolutionsVERSA Integrated Solutions is a premier provider of Information Technology, Artificial Intelligence, Cybersecurity, Cloud, Data Analytics, and Engineering services supporting Federal Government agencies. We help agencies modernize operations through innovative technologies, secure architectures, and mission-driven solutions. Our teams work on high-impact initiatives that improve decision-making, operational efficiency, and citizen services.Position SummaryVERSA Integrated Solutions is seeking an experienced AI/ML Engineer to design, develop, deploy, and maintain Artificial Intelligence (AI) and Machine Learning (ML) solutions supporting Federal Government customers. The successful candidate will work closely with data scientists, software engineers, cloud architects, cybersecurity professionals, and business stakeholders to build intelligent applications that leverage predictive analytics, machine learning, generative AI, and large language models (LLMs).The AI/ML Engineer will support the full lifecycle of AI solutions&mdash;from data preparation and model development to deployment, monitoring, optimization, and governance&mdash;while ensuring compliance with federal security, privacy, and Responsible AI requirements.Position ObjectivesThe AI/ML Engineer will:<ul><li>Design and implement scalable AI and ML solutions.&bull; Build and optimize machine learning models for structured and unstructured data.&bull; Develop data pipelines to support AI workloads.&bull; Integrate AI capabilities into enterprise applications.&bull; Ensure AI solutions comply with federal security, privacy, and governance requirements.&bull; Collaborate with cross-functional teams to deliver mission-focused outcomes.</li></ul>Major Duties &amp; ResponsibilitiesAI &amp; Machine Learning Development<ul><li>Design, develop, train, test, and deploy machine learning models.&bull; Build supervised, unsupervised, reinforcement learning, and deep learning solutions.&bull; Develop predictive analytics and classification models.&bull; Optimize model performance and accuracy through feature engineering and hyperparameter tuning.&bull; Build reusable AI components and services.</li></ul>Generative AI &amp; Large Language Models<ul><li>Develop solutions using Large Language Models (LLMs).&bull; Implement Retrieval-Augmented Generation (RAG) architectures.&bull; Engineer prompts and fine-tune models where appropriate.&bull; Evaluate AI model outputs for accuracy, explainability, and bias.&bull; Support secure deployment of generative AI capabilities.</li></ul>Data Engineering &amp; Preparation<ul><li>Build and maintain data ingestion and transformation pipelines.&bull; Clean, normalize, and prepare structured and unstructured datasets.&bull; Collaborate with Data Engineers to optimize data availability and quality.&bull; Implement feature stores and model-ready datasets.</li></ul>MLOps &amp; Model Lifecycle Management<ul><li>Automate model training, testing, deployment, and monitoring.&bull; Develop CI/CD pipelines for machine learning solutions.&bull; Monitor model drift, performance degradation, and retraining needs.&bull; Maintain version control for models, datasets, and code.</li></ul>Responsible AI &amp; Governance<ul><li>Implement Responsible AI principles including fairness, transparency, explainability, and accountability.&bull; Ensure compliance with NIST AI Risk Management Framework, Executive Orders, and agency-specific AI policies.&bull; Document AI models, assumptions, limitations, and validation results.</li></ul>Collaboration &amp; Innovation<ul><li>Partner with software developers, cloud engineers, and business analysts to integrate AI into enterprise solutions.&bull; Present technical findings and recommendations to stakeholders.&bull; Evaluate emerging AI technologies and recommend improvements.</li></ul>Required Technical Skills<ul><li>Python&bull; SQL&bull; TensorFlow&bull; PyTorch&bull; Scikit-learn&bull; Pandas&bull; NumPy&bull; Hugging Face Transformers&bull; LangChain or similar orchestration frameworks&bull; Azure AI Services or Azure Machine Learning&bull; AWS SageMaker (preferred)&bull; Git/GitHub&bull; Docker&bull; Kubernetes&bull; RESTful APIs</li></ul>Preferred Skills<ul><li>Experience with Retrieval-Augmented Generation (RAG)&bull; Prompt engineering for LLMs&bull; Vector databases (e.g., Pinecone, Azure AI Search)&bull; Knowledge graph integration&bull; Natural Language Processing (NLP)&bull; Computer Vision&bull; Time-series forecasting&bull; Knowledge of FedRAMP and Zero Trust environments</li></ul>Required Qualifications<ul><li>Strong analytical and problem-solving skills.&bull; Excellent written and verbal communication skills.&bull; Ability to translate business requirements into AI-driven technical solutions.&bull; Experience working in Agile/DevSecOps environments.&bull; Experience supporting federal government customers is highly desirable.</li></ul>EducationBachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Mathematics, Statistics, or a related field. A Master's degree is preferred. Equivalent experience may be substituted for education.Experience LevelsJunior (0&ndash;4 Years)<ul><li>Experience with Python and machine learning fundamentals.&bull; Exposure to cloud platforms and data science tools.&bull; Participation in AI/ML projects through coursework, internships, or professional experience.</li></ul>Intermediate (5&ndash;9 Years)<ul><li>Development and deployment of production AI/ML models.&bull; Experience with MLOps pipelines and cloud AI services.&bull; Collaboration with cross-functional software development teams.</li></ul>Senior (10&ndash;14 Years)<ul><li>Leadership in designing enterprise AI solutions.&bull; Expertise in generative AI, LLMs, and Responsible AI practices.&bull; Experience mentoring junior engineers and leading technical initiatives.</li></ul>Subject Matter Expert (15+ Years)<ul><li>Recognized authority in enterprise AI strategy and implementation.&bull; Experience shaping AI governance and modernization initiatives for large organizations.&bull; Trusted advisor to executive leadership on AI adoption and emerging technologies.</li></ul>Preferred Certifications<ul><li>Microsoft Certified: Azure AI Engineer Associate&bull; Microsoft Certified: Azure Data Scientist Associate&bull; AWS Certified Machine Learning &ndash; Specialty&bull; Google Professional Machine Learning Engineer&bull; TensorFlow Developer Certificate&bull; Databricks Certified Machine Learning Professional&bull; ITIL&reg; 4 Foundation (preferred)</li></ul>Desired Federal ExperienceExperience supporting one or more of the following agencies is highly desirable:<ul><li>U.S. Census Bureau&bull; National Institutes of Health (NIH)&bull; Centers for Medicare &amp; Medicaid Services (CMS)&bull; Department of Commerce&bull; Department of Homeland Security (DHS)&bull; Department of Defense (DoD)&bull; Department of Labor (DOL)</li></ul>Security Clearance<ul><li>Ability to obtain and maintain a Public Trust or higherclearance, depending on customer requirements.</li></ul>Work Environment<ul><li>Hybrid or onsite within the Washington, DC Metro Area based on customer requirements.&bull; Collaborative, fast-paced environment supporting mission-critical federal AI initiatives.&bull; Occasional travel to customer sites may be required.</li></ul>Why Join VERSA?At VERSA, you'll work alongside experts delivering innovative AI solutions that help federal agencies solve complex mission challenges. We invest in continuous learning, professional certifications, and opportunities to work with cutting-edge technologies, including machine learning, generative AI, cloud platforms, and advanced analytics.Equal Employment OpportunityVERSA Integrated Solutions is an Equal Opportunity Employer. We are committed to creating an inclusive workplace where all employees are respected, valued, and empowered to succeed. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other status protected by applicable law.Pay: $118,467.98 - $142,671.13 per yearBenefits:<ul><li>401(k)</li><li>401(k) matching</li><li>Dental insurance</li><li>Health insurance</li><li>Paid time off</li><li>Retirement plan</li></ul>Work Location: Hybrid remote in Washington, DC 20591

Software Engineer - Data, AI/ML & Analytics

Deloitte

<div>As organizations adopt generative AI, securing how AI agents, models, and automated workflows access enterprise systems and data has become a core engineering challenge. As an Identity &amp; Gen AI Engineer, you will build generative AI solutions with identity, access, and trust engineered in from the start, securing both human and non-human identities and governing how AI agents and GenAI platforms reach data and downstream systems. This role focuses on hands-on engineering, integration, and continuous enhancement of AI solutions in which identity and access controls are a first-class concern. 
 
Work you'll do 
 
As an Identity &amp; Gen AI Engineer on the Identity and Access Management team, you will be responsible for... 
 
<ul><li>Build and integrate generative AI solutions, including LLM applications, retrieval-augmented generation, and AI agents, with secure access to data and downstream systems.</li></ul> 
<ul><li>Engineer authentication, authorization, and identity controls for AI agents, service accounts, and other non-human identities operating across enterprise and cloud environments.</li></ul> 
<ul><li>Develop guardrails for agentic workflows, including scoped permissions, least-privilege access, credential and secrets management, and runtime policy enforcement.</li></ul> 
<ul><li>Implement logging, monitoring, and governance that provide traceability and accountability for AI system actions.</li></ul> 
<ul><li>Collaborate with IAM, security architecture, and data teams to embed identity controls into GenAI solution delivery and operations.</li></ul> 
<ul><li>Create and maintain reference architectures, reusable patterns, and technical documentation for building and securing AI systems.</li></ul> 
A successful candidate would possess these skills: 
<ul><li>
Ability to work independently and collaborate as part of a team</li><li>
Effective written and verbal communication skills</li><li>
Meticulous attention to detail and quality of work product</li><li>
Ability to build and sustain professional relationships</li><li>
Ability to lead projects or workstreams</li><li>
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment</li><li>
Strong interpersonal skills and professional demeanor</li><li>
Ability to meet deadlines</li><li>
Ability to provide clear guidance to others</li></ul> 

The team 
 
Our Deloitte Cyber team understands the unique challenges and opportunities businesses face in cybersecurity. Join our team to deliver powerful solutions to help our clients navigate the ever-changing threat landscape. Through powerful solutions and managed services that simplify complexity, we enable our clients to operate with resilience, grow with confidence, and proactively manage to secure success. 
 
Our Digital Trust &amp; Privacy offering enables trust and safety of online communications and digital products, protecting users, consumers, and patients from harm. Enables clients to provide consumer confidence in knowing with whom they are dealing and ensuring the integrity of access to data. 
 
Qualifications 
 
Required: 
<ul><li>
Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a similar technical field</li><li>
Ability to work onsite up to 5 days a week.</li><li>
3+ years of software engineering experience with Python or a comparable language
</li><li>1+ year of hands-on experience building, integrating, or deploying generative AI solutions such as large language model (LLM) applications, retrieval-augmented generation (RAG), or AI agents, including use of model APIs, orchestration frameworks, and AI development tools such as Claude Code, OpenAI Codex, GitHub Copilot, or Cursor
</li><li>Working knowledge of identity and access management concepts and protocols, including authentication, authorization, single sign-on (SSO), and standards such as OpenID Connect (OIDC), Security Assertion Markup Language (SAML), OAuth, and JSON Web Token (JWT)
</li><li>Ability to travel 15%, on average, based on the work you do and the clients and industries/sectors you serve.
</li><li>Ability to obtain and maintain the necessary security clearance.
</li><li>Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.</li></ul> 
Preferred: 
<ul><li>
Experience deploying generative AI solutions to production environments
</li><li>Hands-on experience with identity and access management platforms such as SailPoint, Okta, or Microsoft Entra ID
</li><li>Experience securing non-human or machine identities, service accounts, secrets, and credentials using tools such as HashiCorp Vault or CyberArk
</li><li>Experience with AI agent frameworks and protocols such as LangChain, LangGraph, or Model Context Protocol (MCP)
</li><li>Experience with fine-grained authorization or policy-as-code using tools such as Open Policy Agent (OPA), Cedar, or OpenFGA
</li><li>Familiarity with AI and LLM security risks such as the OWASP Top 10 for LLM Applications, prompt injection, and excessive agency
</li><li>Experience applying AI governance and risk frameworks such as the NIST AI Risk Management Framework (AI RMF)
</li><li>2+ years of experience building or deploying workloads in cloud environments such as Amazon Web Services (AWS) and Microsoft Azure
</li><li>Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP), or a cloud engineering certification such as AWS Certified Solutions Architect or Microsoft Certified: Azure Solutions Architect
</li><li>1+ year of experience supporting federal government environments
</li>1+ year of experience with infrastructure-as-code or automation technologies such as Terraform or Ansible 
<li>
</li></ul> 
 
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $105,400 to $207,800. 
 
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.</div>

Senior Consultant, Strategy, Growth, and Transformation, Identity & Gen AI Engineer

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