This position requires an ACTIVE SECRET security clearance. Your application will not be reviewed if you do not have an ACTIVE security clearance at SECRET or above.
Elevate Government Solutions is a high growth Technology Services company focused on driving technological change in the government space. Our teams engage with various government agencies to develop and deploy emerging technology solutions using a tailored Agile methodology.
We are seeking a Senior Agentic AI Engineer to lead the technical design, prototyping, and deployment of autonomous and semi-autonomous AI workflows supporting a federal financial crimes focused agency. In this high-impact role, you will be instrumental in executing an agentic foundation initiative, transitioning the client from productivity tools into an autonomous, ontology-driven fraud detection and targeting ecosystem. Working on a modern AWS GovCloud or Databricks Lakehouse foundation, you will architect multi-agent systems that autonomously triage, auto-tag, and analyze Bank Secrecy Act (BSA) data and Suspicious Activity Reports (SARs). You will implement advanced agentic patterns - such as ontology traversal, entity resolution, iterative hypothesis generation, and tool use - to reduce analyst investigation cycles from weeks and months down to hours and days.
Responsibilities and Duties
- Agentic Architecture & Orchestration
- Architect and scale multi-agent systems driving the agentic foundation, including autonomous agent task routing, iterative planning, reflection, and human-in-the-loop validation.
- Develop specialized agents capable of parsing complex unstructured narratives in SARs, extracting key entities, and applying structured fraud ontologies for automated tagging.
- Implement agent coordination pipelines using frameworks such as LangGraph, AutoGen, CrewAI, or Amazon Bedrock Agents with deterministic fallback logic and schema enforcement.
- BSA & SAR Fraud Targeting Integration
- Bridge agent reasoning with the client's Lakehouse data platform, designing tools and APIs for agents to interrogate high-volume BSA datasets, target data selection notebooks, and risk-ranking pipelines.
- Integrate graph-based ontologies and entity resolution services into reasoning workflows to trace illicit financial networks, anomalous filers, and typologies across BSA filings.
- Support downstream analytic applications including accelerating Foreign Target Assessments (FTAs), Section 311 actions, open request letters, and regulatory comment review.
- Secure AWS Cloud & Lakehouse Deployment
- Deploy production agentic solutions on AWS GovCloud, orchestrating foundation models via Amazon Bedrock.
- Collaborate with data engineering teams to query and interface with Databricks Lakehouse / Delta tables hosting BSA and SPCL data under active Authority to Operate (ATO) guidelines.
- Implement Infrastructure as Code (Terraform or AWS CloudFormation/CDK) and ensure strict compliance with federal zero-trust, RBAC/ABAC, and FedRAMP High security baselines.
- SI O&M, Model Evaluation, & Guardrails
- Design systematic evaluation benchmarks to monitor agent tool-selection accuracy, hallucination rates, and ontology alignment.
- Support ongoing SI Operations & Maintenance (O&M) by calibrating guardrails, managing model risk management (MRM) documentation, and evaluating new foundation model releases.
Required Experience, Skills and Qualifications
- Active U.S. Government Secret clearance (with ability to obtain and maintain agency suitability/security vetting).
- 5+ years of software engineering experience with deep expertise in Python.
- 2+ years of hands-on experience designing and operationalizing Generative AI and LLM solutions.
- Demonstrated experience implementing agentic workflows (e.g., tool/function calling, memory management, multi-agent coordination with LangGraph, AutoGen, CrewAI, or Bedrock Agents).
- Experience in AWS environments (Bedrock, SageMaker, OpenSearch, Lambda, Step Functions, S3, IAM).
- Experience working with structured vector databases and semantic search pipelines over large unstructured narrative collections.
- Ability to work East Coast hours
- Ability to work hybrid in Vienna, VA, or remotely
Preferred Qualifications
- Financial Crimes Domain: Direct experience working with Bank Secrecy Act (BSA) data, Suspicious Activity Reports (SARs), Anti-Money Laundering (AML), Counter-Terrorist Financing (CTF), or federal fraud analytics.
- Ontologies & Entity Resolution: Hands-on experience integrating knowledge graphs, semantic ontologies, or entity resolution algorithms (e.g., Senzing, Neo4j, Amazon Neptune) into LLM reasoning loops.
- Lakehouse Integration: Familiarity with Databricks, Apache Spark, Delta Lake, or lakehouse architectures deployed within federal cloud environments.
- Federal Compliance: Familiarity with Federal AI Executive Orders, NIST AI Risk Management Framework (RMF), and secure enclaves (FedRAMP High / GovCloud).
- Active AWS Certified Solutions Architect or Machine Learning Specialty certifications.
Education Requirement
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical discipline.
Benefits
- Health Insurance
- 401k match
- Unlimited Vacation
- 11 Federal Holidays
- Remote work
- Training
- Mentoring/Coaching