Junior AI Engineer - Agentic Platform

belaytechnologies; Maryland; On-site; USD 70,000 - 190,000; Full time

Benefits offered by this job

Paid leave

401(k) match

Tuition assistance

Student loan repayment

Company-funded HSA

Health insurance

Dental coverage

Life insurance

Gym reimbursements

Team events

Job summary

Belay Technologies is seeking a Junior Software Engineer to join our intel team and help build a cutting‑edge agentic platform that powers autonomous workflows. You will integrate diverse data sources and external APIs to enable scalable system interoperability.

You will work with cyber analysts to translate operational challenges into effective technical solutions, implementing agentic primitives, prompts, and subagents to create context‑aware capabilities in a fast‑moving AI environment.

Qualifications

• TS/SCI clearance with polygraph.
• 12 years, B.S. in a technical discipline or 4 additional years in place of B.S.

Responsibilities

• Develop agentic integrations with Python that leverage multiple AI models, APIs, and data sources in production.
• Build tools and agentic workflows within modern frameworks like PydanticAI, Langgraph, and DeepAgents.
• Work directly with stakeholders and cyber analysts to understand workflows and identify automation opportunities.
• Design and implement real‑time analytics pipelines in Python leveraging Apache Kafka for stream processing and Elasticsearch for indexing and querying.
• Maintain and troubleshoot a production‑grade agentic platform.

Skills

Python proficiency

Production apps

AI development concepts

Stream processing

AI coding assistants

Education

B.S. in technical discipline

Tools

PydanticAI

Langgraph

DeepAgents

Job description

Belay Technologies is seeking a Junior Software Engineer to join our intel team and help build a cutting‑edge agentic platform that powers autonomous workflows. You will integrate diverse data sources and external APIs to enable scalable system interoperability.

You will work with cyber analysts to translate operational challenges into effective technical solutions, implementing agentic primitives, prompts, and subagents to create context‑aware capabilities in a fast‑moving AI environment.