AI Solutions Engineer

About the job AI Solutions Engineer

ExeQut is a leader in consulting, delivering customized solutions and systems integration for enterprise applications, data & AI platforms, identity access and management, cybersecurity, and software development. We emphasize transparency, collaboration, and addressing core business challenges through a structured, agile development process. Our clients include federal civilian agencies, commercial enterprises in healthcare IT and financial services, and state/local government entities seeking complex technology solutions that deliver real impact. Partnering with clients from ideation to deployment, we ensure our solutions deliver long-term value and streamline the user experience.

Key Responsibilities

• Sit in client discovery sessions, identify the real technical problem, and design the solution architecture, on the spot if needed.
• Build working proofs of concept and prototypes using Python, AWS services, and modern AI/ML frameworks
• Design and implement data pipelines, RAG systems, agentic workflows, API layers, and cloud infrastructure on AWS
• Write technical proposal volumes and statements of work that are specific, credible, and win contracts
• Present architectures and demos to mixed audiences, federal CTOs, program managers, and technical evaluation committees
• Contribute to shaping ExeQut's service offerings, reusable solution accelerators, and technical marketing materials
• Stay sharp on the AI landscape: new models, frameworks, deployment patterns, cost optimization, and bring that knowledge into every client conversation

Qualifications & Requirements

• You can build. 5+ years of hands-on experience designing and implementing solutions in cloud environments (AWS strongly preferred). You can write code, deploy infrastructure, and debug production issues.
• You know AI/ML beyond the buzzwords. Direct experience building RAG pipelines, working with LLMs (fine-tuning, prompt engineering, evaluation), designing data pipelines, or deploying ML models. You can explain the difference between vector search options, when to use Bedrock vs SageMaker, and why chunking strategy matters.
• You're fluent with AI-assisted development. You actively use tools like Claude Code, Cursor, GitHub Copilot, or similar IDE-integrated AI to accelerate your work. You know how to direct these tools effectively, catch when they're wrong, and ship production-quality output faster because of them.
• You can architect on a whiteboard. Given a business problem, you can sketch a complete system architecture — ingestion, processing, storage, serving, security — and explain every decision to a technical or non-technical audience.
• You can write and present. Clear technical writing for proposals and SOWs.
• Confident presenting to rooms that include both executives and engineers.
• AWS depth. You know the AWS ecosystem well — ECS/Fargate, Lambda, API Gateway, S3, DynamoDB, RDS/Aurora, CloudFront, IAM, VPC networking, and Bedrock and/or SageMaker. AWS certifications (SA Associate or Professional) are a strong plus.
• Experience with Federal civilian or SLED clients, including familiarity with FedRAMP, ATOs, and GovCloud constraints
• Experience writing technical volumes for government proposals and understanding evaluation criteria
• Background in data engineering — building ETL/ELT pipelines, working with structured and unstructured data at scale
• Familiarity with Python ecosystem for AI/ML: LangChain/LangGraph, FAISS/pgvector/OpenSearch, Hugging Face, PyTorch
• Experience with IaC (Terraform, CloudFormation, CDK) and CI/CD pipelines
• 2+ years in a consulting, pre-sales, or client-facing technical role

How We'll Evaluate You

We don't do trivia interviews. Here's what to expect:

1. Technical conversation: We'll talk through your past projects. Be ready to go deep on architectures you've personally designed and built. We'll ask why a lot.
2. Liv build exercise: We'll give you a realistic client scenario and ask you to architect and start building the solution using whatever AI-assisted tools you prefer. We want to see how you think, how you use tools, and how you handle ambiguity.
3. Client simulation: We'll role-play a client meeting where you need to present a technical solution to a mixed audience and handle pushback.

The ideal candidate is based in the metropolitan Washington, DC area. They are expected to travel as needed to client sites and to our offices in Maryland and Virginia.

Compensation

$150,000 base with target $30,000-$45,000 variable

Why Join ExeQut?

If you are a driven professional with a passion for Data & AI solutions, and you want to make an impact by working on high-profile projects across North America, we'd love to hear from you.