Senior Agentic AI Engineer

Elevate Government Solutions; Washington (District of Columbia); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health Insurance

Unlimited Vacation

Training

Mentoring/Coaching

Job summary

Elevate Government Solutions is seeking a Senior Agentic AI Engineer to lead design, prototyping, and deployment of autonomous AI workflows supporting a federal financial crimes agency.

You will work on a modern AWS GovCloud or Databricks Lakehouse foundation, architect multi-agent systems for automated tagging, entity resolution, and risk ranking of BSA data. Remote or Vienna, VA hybrid work is supported.

Qualifications

• Active U.S. Government Secret clearance required.
• 5+ years software engineering with Python.
• 2+ years designing/operationalizing Generative AI/LLMs.
• Experience implementing agentic workflows and multi-agent coordination.
• AWS GovCloud, Lakehouse data platforms, and secure deployment experience.

Responsibilities

• Architect and scale multi-agent systems with autonomous task routing and human-in-the-loop validation.
• Develop agents to parse SARs, extract entities, and apply fraud ontologies.
• Implement coordination pipelines with LangGraph, AutoGen, CrewAI, or Bedrock Agents.
• Bridge agent reasoning with Databricks Lakehouse data and risk-ranking pipelines.
• Ensure FedRAMP High security and zero-trust posture in deployment.

Skills

Python

Generative AI

Agentic workflows

DS/ML concepts

Cloud architectures

Education

Bachelor’s or Master’s degree in Computer Science/AI/Data Science/Software Engineering

Tools

LangGraph

AutoGen

CrewAI

Bedrock Agents

Databricks Lakehouse

Job description

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

1. 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.
• 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.

3. 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.
• 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.
• Health Insurance
• Unlimited Vacation
• Training
• Mentoring/Coaching