The business and/or technical problem the job is looking to solve is to build, test, and deploy AI applications and services, translating solution designs and reference architectures into working, demo-ready components for potential clients.
Requirements
- Minimum THREE (3) years of experience in software, data, or ML engineering, including building and operating cloud-native services.
- 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.
- Ability to obtain and maintain a Federal or DoD SECRET security clearance; active clearance preferred.
Responsibilities
- 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.
Other
- Up to 10% travel
- US Citizenship is required
- Bachelor’s degree is required.
- Growth mindset with interest in expanding into broader architecture responsibilities over time.
- Certifications in cloud architecture, DevOps, or AI/ML (e.g., AWS/Azure/GCP, Databricks, Kubernetes).
