Job Description
Job Description
Job Overview:
Pay Range: $60hr - $65hr
Requirement/Must Have:
- 3+ years of experience building production backend or distributed systems with pre-AI experience.
- Proven experience shipping AI/LLM features serving real users at scale, not just prototypes or demos.
- Experience building AI agents, skills, tools, or MCP (Model Context Protocol) integrations.
- Strong proficiency in Python for backend development.
- Working knowledge of Go, TypeScript, or Rust.
- Deep experience with AWS, GCP, or Azure, including cost optimization and compute decisions.
- Hands-on experience with Docker and Kubernetes, including building, deploying, debugging, and scaling services.
- Strong understanding of LLM integration, including token economics, context limits, rate limiting, structured outputs, and API failure modes.
- Strong understanding of LLM evaluation, including non-determinism, quality measurement, and regression detection.
- Hands-on engineering mindset with the ability to write code, debug production issues, and deploy work independently.
Responsibilities:
- Build intelligent, data-driven platform capabilities for next-generation test analytics and test agents.
- Develop automated evaluation tools for AI and human-based assessment systems.
- Conduct rigorous statistical analyses to ensure reliability and performance.
- Benchmark, adapt, and integrate AI/ML models into existing software systems.
- Independently run and analyze ML experiments to drive real improvements.
- Build scalable infrastructure for Generative AI systems connecting test stations, line-level data, and pipelines.
- Deploy, manage, and scale AI services in production environments.
Should Have:
- Experience building multi-step agentic workflows with tool use and function calling.
- Experience with agent orchestration frameworks such as LangGraph, CrewAI, or custom frameworks.
- Experience building guardrails, fallbacks, or graceful degradation for AI systems.
- Experience with streaming inference and async agent orchestration.
- Experience with cost and latency optimization techniques such as caching, batching, and prompt compression.
- Familiarity with ML observability tools such as Langfuse, Arize, Braintrust, and Weights & Biases.
- Experience with retrieval systems such as vector search and hybrid search.
Skills:
- Python.
- Go.
- TypeScript.
- Rust.
- AWS.
- GCP.
- Azure.
- Docker.
- Kubernetes.
- AI/LLM integration.
- Agentic systems.
- MCP integrations.
- ML experimentation.
- Statistical analysis.
- CI/CD and scalable infrastructure.
Qualification and Education:
- Strong engineering background with hands-on experience in backend systems, AI systems, and cloud-native infrastructure.
Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading staffing and recruiting powerhouse. Proudly recognized as a nationally and locally certified diversity firm, Cynet delivers agile, scalable talent solutions across industries. With an active footprint in all 50 U.S. states and Canada, we support thousands of consultants through our expansive, high-performing recruitment engine operating across North America and Asia—ensuring speed, quality, and consistency in every hire.