AI Engineer

Job Description

Job Family: Software Development & Support Travel Required: Up to 10% Clearance Required: None What You Will Do: Build, test, and deploy AI applications and services, translating solution designs and reference architectures into working, demo-ready components. Implement data and ML pipelines (ingest, transform, feature stores, vector indexes) and wire up retrieval-augmented generation (RAG) and agentic workflows. Package and serve models (LLMs and traditional ML) via APIs and microservices using containers and orchestration (e.

g. , Docker, Kubernetes). Stand up and maintain cloud resources and AI platforms (AWS, Azure, GCP; Palantir; Databricks), including CI/CD, IaC (e. g.

, Terraform), secrets, and observability. Integrate AI capabilities (prompt orchestration, tool/function calling, embeddings, fine-tuning) into applications and services.

Collaborate with data scientists, platform engineers, and product teams to iterate on use cases, deliver POCs/MVPs, and harden them for scale. Contribute to demos, technical documentation, and solution content for proposals and pitch materials. Follow responsible AI practices and security/compliance requirements across commercial and public sector environments.

What You Will Need: Bachelor’s degree is required. Minimum Four (4) years of experience in software, data, or ML engineering, including building and operating cloud-native services or Master’s degree and Minimum TWO (2) years of experience Minimum ONE (1) year of hands-on experience with Generative AI and/or agentic patterns (e. g.

, RAG, function/tool calling, prompt orchestration). Proficiency with at least one major cloud (AWS, Azure, or GCP) and modern DevOps practices (Git, CI/CD, containerization, infrastructure as code).

Strong programming skills in Python and/or TypeScript/JavaScript; comfort working with APIs, SDKs, and common data formats. Familiarity with vector databases and embeddings and LLM application frameworks. Ability to troubleshoot production systems (logs, metrics, traces), write clear documentation/runbooks, and collaborate in cross-functional teams.

Growth mindset with interest in expanding into broader architecture responsibilities over time. What Would Be Nice To Have: Ability to obtain and maintain a Federal or DoD SECRET security clearance; active clearance preferred. Certifications in cloud architecture, DevOps, or AI/ML (e.

g. , AWS/Azure/GCP, Databricks, Kubernetes). Experience contributing to client-facing engineering in consulting or product environments.

Master’s degree The annual salary range for this position is $98,000. 00-$163,000. 00.

EWJD3