Healthcare Ai

Healthcare Ai Data Jobs

2 jobs found

Today

Agentic AI Engineer

Motion Recruitment Charlotte, NC

Charlotte, NC

Today

Full time Agentic Ai Agentic Ai Orchestration Ai Agent

Apply Now

Job Description

The Agentic AI Engineer will design, build, deploy, and maintain AI-powered agents and multi-agent systems that automate business processes and integrate with enterprise applications. The role is hands on and includes HIPAA-aware, secure development, along with agent development, platform engineering and observability, and collaboration through documentation.

Responsibilities

Design and build AI agents using LLMs and agent frameworks including LangChain, LangGraph, CrewAI, and AutoGen.
Develop multi-agent workflows for enterprise use cases such as insurance reconciliation, clinical record summarization, and procurement automation.
Implement agent capabilities including reasoning, planning, memory, and tool use.
Connect agents to enterprise systems, including Salesforce, HubSpot, EMR systems, internal APIs, databases, and SaaS applications.
Build RAG solutions using company knowledge bases.
Apply HIPAA-aware development practices such as RBAC, audit logging, least-privilege tool access, and prompt-injection defense.
Monitor agent performance, reliability, and cost by building evaluation and observability frameworks.
Rapidly prototype and iterate on AI-driven workflows with direct input from business stakeholders.
Mentor junior developers on agentic AI development practices.

Time allocation: 70% AI Agent Development & Enterprise Integration, 20% Platform Engineering & Observability, 10% Collaboration & Documentation. 100% hands on.

Required Skills & Experience

Python
LLM APIs (OpenAI, Anthropic, Google, etc.)
LangChain / LangGraph
CrewAI / AutoGen / Microsoft Agent Framework
API Integration
SQL / Database knowledge
Cloud platforms (AWS, Azure, or GCP)
MCP-enabled systems
Healthcare / Dental EMR systems (e.g., DSN Cloud, WinOMS)

Desired Skills

3-5+ years of software engineering experience
BS or MS in Computer Science or related field
Experience with vector databases (Pinecone, Weaviate, pgvector)
Retrieval-Augmented Generation (RAG) architectures
Containerization (Docker / Kubernetes)
CI/CD and DevOps practices
Prompt engineering and model tuning
Agent evaluation frameworks
Knowledge graph implementation
Familiarity with AI coding tools (Codex, Claude Code, Cursor)
Strong communicator and self-starter

Technologies

Python, LLM APIs, OpenAI, Anthropic, Google, LangChain, LangGraph, CrewAI, AutoGen, Microsoft Agent Framework, SQL, AWS, Azure, GCP, MCP-enabled Systems, DSN Cloud, WinOMS, Salesforce, HubSpot, RAG, HIPAA, RBAC.

Benefits

Competitive Base Salary + Bonus + Equity / Long-Term Incentive
Medical Insurance
Dental Benefits
Vision Benefits
Paid Time Off (PTO)

Location

Charlotte, NC (onsite)

View full job page →

1d ago

Senior Applied AI Engineer

Curai Remote 🌍 Remote

Remote

1d ago

$175k - $200k/yr Full time Senior Artificial Intelligence Fine Tuning

Apply Now

Job Description

Curai is seeking a Senior Applied AI Engineer to design, build, and ship machine learning and LLM systems that influence how clinicians and patients engage with its healthcare platform. This role covers the full lifecycle, from problem framing and data exploration to training, evaluation, production inference, and measurement of real-world clinical and product impact.

Key Responsibilities

Lead the technical execution of complex AI initiatives, owning solution design and delivery within a product or technical domain, while collaborating with senior engineers on broader architectural direction.
Design, build, train, evaluate, and improve advanced machine learning and LLM-based systems for patient and provider-facing products, including use cases such as conversational AI, personalization, user understanding, clinical decision support, and chronic care management.
Own end-to-end problem work: scope with clinicians and product partners, create datasets and evaluations, iterate on modeling, and ship to production with appropriate monitoring and guardrails.
Develop robust evaluation frameworks, including offline benchmarks, human-in-the-loop review, and online experiments, to support confidence in model safety, accuracy, and ongoing improvement.
Build and enhance the team’s platform to accelerate delivery, including data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers.
Partner across clinicians, product, and engineering to translate medical and operational requirements into ML work and deliver measurable improvements to patient and clinician experience.
Provide technical direction for your area, mentor other engineers, and strengthen engineering and scientific rigor, with leadership scope that increases with seniority.
Stay current with the literature and the fast-moving AI ecosystem, and bring forward the most relevant ideas for patients and the team.

Required Qualifications

Bachelor’s degree in Computer Science, Software Engineering, Math, or a related technical degree.
3+ years of hands-on engineering experience, including 1+ years building and deploying machine learning systems with generative AI (LLMs), and a clear track record of impact.
Strong software engineering fundamentals, with the ability to ship reliable, well-tested Python (or comparable language) code in production.
Practical knowledge of modern LLM methods, including prompting, retrieval-augmented generation, fine-tuning, and evaluation, plus awareness of their trade-offs.
Ability to work with messy, real-world data and design evaluations that determine whether a system is actually working.
Strong written and verbal communication skills, including cross-collaboration with clinicians, product managers, and engineers.
A bias toward action and ownership, including the ability to take an ambiguous problem to a result and bring others along.
Motivation to align work with improved health outcomes for real patients.

Technologies

Python
LLMs
Retrieval-augmented generation
Prompting
Fine-tuning
Evaluation

Preferred Qualifications

Experience applying ML or LLMs in healthcare, life sciences, or another regulated, high-stakes domain.
Experience with clinical NLP, medical knowledge representation, or working with electronic health record data.
Experience building agentic systems and tool-using LLMs in production.
Experience scaling ML infrastructure, including training pipelines, distributed inference, and evaluation platforms, for a small, fast-moving team.
Track record of technical leadership, such as setting direction across teams, mentoring engineers, or publishing influential work.

Benefits

High-ownership work on meaningful problems with a tight feedback loop from real clinicians and patients.
A small, senior team where work shows up in the product quickly.
Competitive compensation, meaningful equity, and comprehensive benefits.
Remote-first, flexible work environment across the U.S.
Comprehensive medical, dental, and vision coverage.
Flexible spending plans.
Generous and flexible Paid Time Off (PTO), floating holidays, and parental leave.
401k plan with employer matching.
100% remote, work from home.

Compensation

USD 175,000 - 200,000 per year. Actual base salary will depend on qualifications and years of relevant experience.

Location

Remote (remote), across the U.S.

View full job page →

Healthcare Ai Data Jobs

Agentic AI Engineer

Senior Applied AI Engineer

Get Healthcare Ai Data Jobs alerts