
Staff AI Engineer
Remote · USFull-time$210–280K/yrSeen 1w agoSeen in employer's feed 6 days ago
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At a glance
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Job overview
Machinify is hiring an AI Engineer to build and ship LLM-powered products, turning models, prompts, and retrieval into reliable production systems. The role includes developing LLM applications and infrastructure, evaluating and integrating foundation models, and partnering with product and design on AI-specific user experiences. The posting describes the company as digital-first and says employees can work from anywhere in the US.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Experience Required
None
Minimum Education Required
High School Diploma/G.E.D.
Compensation
$7.25 / hourly
Hours Per Week
40
Number Of Positions
1
Work Schedule and Shift Requirements
First (Day)
Job Description
Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We're constantly reimagining what's possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
We're hiring an AI Engineer to build LLM-powered products that actually ship. You'll live at the seam between research and production - turning models, prompts, and retrieval into reliable systems users depend on. Less "train a m odel from scratch," more "make foundation models do useful work at scale, cheaply, and without hallucinating."
What you'll do
Design and build LLM applications: RAG pipelines, agents, tool-use systems, structured generation, multi-step workflows
Own prompt engineering and evaluation - write evals before you write prompts, and treat both as code
Integrate foundation models (Claude, GPT, Gemini, open-weight Llama/Qwen/Mistral) and know when to reach for which
Build the unglamorous infrastructure that makes LLMs production-grade: caching, streaming, retries, fallbacks, cost controls, observability, guardrails
Fine-tune or distill models when prompting hits a wall (LoRA/QLoRA, SFT, DPO)
Partner with product and design on UX patterns specific to AI (latency masking, streaming UIs, confidence display, human-in-the-loop)
What we're looking for
3+ years of software engineering, with at least 1 year shipping LLM-based features in production
Strong Python and TypeScript; comfortable in a real codebase, not just notebooks
Deep practical knowledge of the LLM stack: prompting techniques, function calling, structured outputs, context management, embedding models, vector search
Have built and maintained an eval suite - and have opinions on why most public benchmarks are misleading
Comfortable with at least one orchestration approach (custom, LangGraph, Inngest, Temporal) and one vector store (pgvector, Pinecone, Turbopuffer, Weaviate)
Cost- and latency-aware: can read a token bill and a trace and know where to cut
Clear communicator who can push back when "just add AI" isn't the right answer
Nice to have
Experience with agent frameworks and MCP (M Odel Context Protocol)
Fine-tuning experience on open-weight models, or work with inference servers like vLLM/TGI/SGLang
Background in security, evals, or red-teaming for LLM systems
Contributions to open-source AI tooling
What we offer
Work from anywhere in the US! Machinify is digital-first.
Top Medical/Dental/Vision offerings
FSA/HSA
Tuition reimbursement
Competitive salary, 401(k) with company match
Unlimited PTO
Additional health and wellness benefits and perks
Flexible and trusting environment where you'll feel empowered to do your best work
The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can range from $210k-$280k+ based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more.
Equal Employment Opportunity at Machinify
We are committed to equal employment opportunity regardless of r ace, color, ancestry, r eligion, s ex, national origin, s exual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at:https://www.machinify.com/candidate-privacy-notice/
Equal Opportunity Employer
Veteran Friendly Employer
Job Type
Full time
Benefits Offered
Not specified
Veteran Preference
No
Place of Work
On-site
Requisition ID
4212332009
How this job compares
Set against the 6,883 open AI Engineer jobs on Olive Jobs, counted October 27, 2026.
- Pay
- This posting$210–280K/yr
- Kentucky median$132–231K/yr36 salary ranges
- US median$133–246K/yr5,668 salary ranges
This range's midpoint, $245K, is 37% above the Kentucky median midpoint ($179K) — in the top quarter of AI Engineer salary ranges in Kentucky.
- Openings
- Olive Jobs lists 47 open AI Engineer jobs in Kentucky and 6,883 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 3 years of experience; AI Engineer postings that state a minimum ask for 5 years at the median (5,921 postings).
- Education
- This posting asks for a high school diploma; 3,374 of the 6,883 open AI Engineer jobs (49%) ask for a high school diploma or higher.
Counted across the open, public US postings on Olive Jobs on October 27, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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