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# Senior AI/ML Engineer

- **Company:** Simpligov Llc
- **Location:** Baltimore, MD, United States (Remote available)
- **Experience:** Expert
- **Salary:** $185,000.0 - $215,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Retention, Software Engineering, Retrieval-Augmented Generation, Large Language Models, Low Latency, Data Pipelines
- **Published:** August 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a0648a097f6507e3

## About the Role

* 5+ years of software engineering with production ownership, including 2+ years shipping LLM or ML-backed features to real users

 * Demonstrated evaluation discipline: you can show how you measured a system, not just that you built it

 * Hands-on depth with modern LLM stacks: agentic patterns, RAG, tool use and function calling, structured outputs, prompt and context engineering

 * Solid backend engineering fundamentals: APIs, data pipelines, observability; you are an engineer first

 * Experience in government, healthcare, or other regulated environments is a plus

## Description

* Design, build, and ship production AI features across the SimpliAI suite: agentic workflows, retrieval-augmented generation, structured extraction, and form and workflow intelligence

 * Build evaluation before features: golden datasets, calibrated LLM-as-judge scoring, and regression evals wired into our observability stack; "it demos well" is not a bar we recognize

 * Own the quality, safety, latency, and cost of what you ship, including per-workload model routing and unit economics

 * Operate inside our compliance boundary: self-hosted observability, GovCloud inference paths (including Amazon Bedrock), and disciplined data retention

 * Work in the open through our Plan-and-Review cadence: written designs, explicit assumptions, uncertainty surfaced early

 * Raise the AI floor of the whole team: reusable patterns, reviews, and shared components, not private magic


## Related Videos

- [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge)
- [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load)
- [Architecting the Future: Leveraging AI, Cloud, and Data for Business Success](https://www.wearedevelopers.com/videos/1096-architecting-the-future-leveraging-ai-cloud-and-data-for-business-success)
- [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions)
- [Three years of putting LLMs into Software - Lessons learned](https://www.wearedevelopers.com/videos/1508-three-years-of-putting-llms-into-software-lessons-learned)
- [Prompt Injection, Poisoning & More: The Dark Side of LLMs](https://www.wearedevelopers.com/videos/1563-prompt-injection-poisoning-more-the-dark-side-of-llms)

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