Remote Solutions Engineer Jobs in Converse, TX (NOW HIRING)

Remote Work:
Yes
Job Number:
R0247584
Location:
San Antonio,TX,US
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Additional Locations:

• Austin, Texas, USA

AWS Agentic AI Platform Engineer
The Opportunity:
As an experienced AI/ML engineer, you know that machine learning and generative AI are critical to understanding and processing large, complex datasets. Your ability to apply statistical learning, large language models, retrieval techniques, and agentic workflow patterns makes you an integral part of delivering secure, customer-focused solutions. We need your technical knowledge and desire to problem-solve to help mission organizations transform fragmented data and manual processes into trustworthy AI-enabled decision support and workflow automation. As an AI/ML engineer on our national security team, you'll train, test, deploy, and maintain machine learning models and agentic applications that learn from data, retrieve governed knowledge, interact with approved tools and services, and support human decision-making.
In this role, you'll own and help define the direction of mission-critical solutions by applying best-fit ML algorithms, foundation models, retrieval architectures, and agent orchestration patterns. You'll be part of a talented team of machine learning engineers across the company and collaborate with data engineers, data scientists, software engineers, cloud and DevSecOps engineers, solutions architects, product owners, and mission subject matter experts to deliver secure AWS-based capabilities that process structured and unstructured data, automate complex workflows, and produce traceable outputs. Your skills and technical expertise will guide clients as they navigate the landscape of AI/ML algorithms, tools, frameworks, evaluation methods, and production deployment patterns.
Work with us to solve real-world challenges and define AI/ML strategy for national defense mission-support operations.
Join us. The world can't wait.
You Have:

• 2+ years of experience with AI/ML engineering, data science, software engineering, data engineering, or cloud engineering
• Experience developing AI/ML applications using Python
• Experience developing agentic AI or large language model applications, retrieval-augmented generation systems, or predictive machine learning models
• Experience integrating AI/ML capabilities with APIs, data stores, cloud services, or enterprise applications
• Experience developing, deploying, or supporting applications on AWS
• Knowledge of AI/ML evaluation methods for model quality, retrieval relevance, task success, latency, cost, or system performance
• Knowledge of software engineering and DevSecOps practices, including version control, automated testing, CI/CD, containerization, and infrastructure as code
• Ability to translate operational needs into testable technical requirements and collaborate with multidisciplinary engineering and mission teams
• Ability to obtain a Secret clearance
• Bachelor's degree

Nice If You Have:

• Experience developing agentic AI applications using AWS Strands Agents, LangGraph, LangChain, LlamaIndex, or comparable frameworks
• Experience with Amazon Bedrock, Amazon SageMaker AI, Amazon OpenSearch Service, Knowledge Bases for Amazon Bedrock, Amazon Bedrock Guardrails, or related AWS AI/ML services
• Experience implementing retrieval-augmented generation, embeddings, vector search, reranking, knowledge graphs, Model Context Protocol, Agent-to-Agent communication, or structured tool-calling integrations
• Experience developing Python APIs, microservices, or durable workflows using FastAPI, Pydantic, OpenAPI, Temporal, AWS Step Functions, Amazon EventBridge, or comparable technologies
• Experience with Docker, Kubernetes, Amazon EKS, Amazon ECS, Terraform, AWS CloudFormation, AWS CDK, or CI/CD automation
• Experience with MLOps or LLMOps, including automated evaluation, prompt or model versioning, observability, tracing, drift monitoring, or rollback controls
• Experience supporting AWS GovCloud, FedRAMP High, DoD Impact Level 4 or 5, or another regulated or high-assurance cloud environment
• Experience with computer vision, multimodal AI, geospatial analytics, graph neural networks, temporal or dynamic graph networks, network science, or social network analysis
• Secret clearance
• AWS AI/ML, Software Development, Architecture, DevOps, Cloud Operations, or Security Certification or CompTIA Security+ Certification

Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.
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.
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