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agentic ai engineer — healthcare ai Jobs in Seattle

agentic ai engineer — healthcare ai

ai / software engineering intern Jobs in Seattle

ai / software engineering intern

aiml - applied ml engineer, data generation & verification Jobs in Seattle

aiml - sr backend engineer, data and ml innovation Jobs in Seattle

aiml - sr machine learning engineer, data and ml innovation Jobs in Seattle

artificial intelligence specialist

Deloitte

<div>
 Three hundred fifty million Americans rely on a healthcare system whose decision-making has become slow, costly, and adversarial - care delayed by prior authorization and paperwork, claims that misfire, clinical decisions made without the right information at the right moment, and patients who struggle to navigate or afford the care they need. Deloitte has a new AI-first effort, backed by $1B in committed investment, building the reasoning models and agentic systems to rebuild how that system decides - across payers, providers, and life sciences, and for the patients they serve - so that care is faster, fairer, and far less wasteful. This is not AI applied at the margins. It is a ground-up rebuild of the decision-making machinery behind American healthcare, at national scale.
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 This is an early, well-funded build. You will own agent systems end to end - from architecture through production - and your work ships into live clinical and operational settings within your first months, not into a lab.
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 As an Agentic AI Engineer, you will design, build, and operationalize the LLM- and SLM-powered systems behind real healthcare decisioning - the reasoning, orchestration, retrieval, memory, and control layers that let intelligent agents operate reliably across the hardest decisions in the industry: clinical reasoning, prior authorization and claims integrity, care navigation, and the operational workflows that run across payers, providers, and life sciences. This is not a prompt-only role. We are looking for builders who think deeply about system behavior, grounding, and reliability where a wrong action has real consequences for patients and the clinicians who serve them.
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 You do not need a healthcare background. We pair every engineer with clinical and domain experts and teach you the domain - you bring the agentic engineering depth.
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 We hire on demonstrated depth, not years - the level you join at is determined through our interview process, based on the depth and judgment you demonstrate, not your years in a title.
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 Work you'll do
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 Agent architecture &amp; orchestration
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 <ul>
  <li>
   Design and implement agentic systems capable of multi-step reasoning, planning, tool use, and workflow execution against complex, regulated operational processes.
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   Build stateful workflows using frameworks such as LangGraph and LangChain - including branching, retries, self-correction, human-in-the-loop checkpoints, and reusable orchestration patterns.
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   Engineer for long-horizon reliability - multi-step task completion, recovery from compounding errors, planning under uncertainty, and robust tool use when individual steps fail.
  </li>
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   Build the reasoning behind regulated decisions - policy- and criteria-grounded outputs, structured proposer/critic/judge-style review, and auditable rationales for high-stakes decisions across the industry, from clinical review and prior authorization to claims integrity and care management.
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  </li>
 </ul>
 Retrieval, grounding &amp; context engineering
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   Develop end-to-end Retrieval-Augmented Generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, contextual compression, and grounding strategies.
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   Engineer memory and context management - conversational state, persistent memory, retrieval-aware context assembly, and token-efficient context selection.
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   Apply modern context-delivery patterns (e.g., MCP-style tool/context interfaces) so agents access the right information at the right time.
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  </li>
 </ul>
 Reliability, evaluation &amp; safety
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 <ul>
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   Implement observability and tracing for prompts, tool calls, retrieval quality, agent traces, failures, drift, latency, and production behavior.
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   Apply guardrails, safety controls, and failure-handling to reduce hallucinations and unsafe actions.
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   Evaluate agents at the trajectory and task level - multi-step task success, failure-mode and regression analysis, and sandboxed test environments - alongside retrieval- and generation-quality metrics, automated checks, and human review.
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   Engineer healthcare-grade safety - deployment eval gates, human-oversight and escalation models, auditability and traceability for regulated decisions, and PHI/HIPAA-aware data handling.
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  </li>
 </ul>
 Integration &amp; production craft
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   Build integrations with internal and external tools, APIs, enterprise systems, databases, and model providers so agents operate safely within real business workflows.
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   Deliver production-quality code with strong practices in testing, CI/CD, logging, versioning, and documentation; make architecture decisions that balance quality, safety, latency, cost, and model risk.
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   Partner with our modeling and post-training engineers to improve model behavior for tool use, grounding, and long-horizon reasoning - through evaluation-driven feedback and, where it helps, fine-tuned or reasoning-optimized models.
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   Translate ambiguous, high-complexity operational processes into robust system logic and reusable AI patterns; stay current with advances in agentic systems and translate research into practical engineering decisions.
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  </li>
 </ul>
 The team
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 Deloitte brings together AI researchers, modeling and platform engineers, architects, clinical and domain specialists, and product leaders to build, deploy, and operate verticalized AI systems across software, data, models, and cloud infrastructure - engineered for one of the most complex operating environments in the world. The work spans the healthcare industry - payers, providers, and life sciences - and involves genuinely hard reasoning problems, nuanced operational workflows, and a high bar for reliability, with little tolerance for shallow or unreliable outputs. We pair frontier AI research with production-grade engineering, and we ship into real clinical and operational settings rather than leaving models in the lab.
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 <strong>
  Required Qualifications
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 </strong>
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  <li>
   Bachelor's degree in Computer Science, Engineering, Data Science, Computational Linguistics, or a related field.
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   Demonstrated depth building and shipping production agentic systems - this is your primary craft, not a recent exploration. We weigh shipped systems, research, model releases, and open source over years in a title; expect strong software/ML fundamentals plus substantial, recent hands-on agentic work.
  </li>
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   Strong, hands-on experience building production agent systems with modern orchestration - LangGraph/LangChain or equivalent, including custom orchestration.
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   Experience designing and optimizing end-to-end RAG systems: indexing, retrieval, reranking, grounding, and evaluation.
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   Strong understanding of memory and context management, including context windows, retrieval-driven context assembly, persistent memory, and high-signal context selection.
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   Deep, practical understanding of LLM behavior - strengths, limitations, hallucination risks, reasoning constraints, and latency/cost trade-offs - and the evaluation methods used to measure them.
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   Experience evaluating and debugging agent behavior - task-success and trajectory analysis, not just output quality.
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   Strong Python engineering skills and modern software practices: testing, CI/CD, version control, and API integration; experience implementing observability, tracing, and debugging for LLM-based systems in production.
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   Hands-on experience with at least one frontier model platform (e.g., Anthropic, Google, OpenAI) and/or open-weight/self-hosted models (e.g., Llama via vLLM), including production tool use and agent capabilities.
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   Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
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   Limited immigration sponsorship may be available.
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  </li>
 </ul>
 <strong>
  Preferred Qualifications
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 </strong>
 <ul>
  <li>
   Experience with multi-agent systems and agent collaboration patterns.
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   Familiarity with vector databases and retrieval infrastructure such as Pinecone, Weaviate, or Milvus.
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   Exposure to model adaptation and fine-tuning techniques such as LoRA or QLoRA.
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   Understanding of traditional NLP concepts: tokenization, semantic similarity, entity extraction, summarization, and transformer fundamentals.
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   Experience operating in highly regulated, high-stakes, or operationally complex environments; healthcare exposure - clinical, payer, or life-sciences workflows, or standards such as FHIR - is a plus, not a requirement.
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   Demonstrated habit of staying current with AI research, benchmarks, and emerging engineering patterns.
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  </li>
 </ul>
 <strong>
  Compensation
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  <br/>
 </strong>
 Base salary is benchmarked to leading technology companies rather than traditional consulting scales, and the role carries a substantial performance-based incentive opportunity designed to grow with the value you help create - startup-style upside, with the backing of a committed, well-capitalized platform. The estimated base salary range is $110,700-$372,900 (not adjusted for geographic differential); actual base pay depends on your skills, experience, and level, and you may also be eligible for a discretionary annual incentive based on individual and organizational performance.
</div>


Agentic AI Engineer — Healthcare AI

turing

<div><div><h1 class="jobSectionHeader"><b>About Turing</b></h1>
<p>
Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com.</p></div><div></div><p><br>
Turing is looking for a Senior Technical Recruiter to join our embedded <b>Research Engineering Recruitment Pod</b>. In this role, you will work side-by-side with our Research Scientists, Research Engineers, and AI leadership to source, engage, and close the talent building at the frontier of AI.</p>
<p>
This is not a high-volume, transactional recruiting role. The talent pool for elite Research Engineers and Forward-Deployed Engineers is highly concentrated, hyper-competitive, and continuously targeted by frontier labs. You will act as an embedded strategic partner, mapping passive talent ecosystems across academia, quantitative research, and open-source networks, developing technically informed candidate pipelines, and orchestrating bespoke closing strategies for candidates who do not move through standard corporate hiring funnels.</p>
<h3 class="jobSectionHeader"><b>
The Anti-Sell</b></h3>
<p>
This is a high-urgency recruiting role. You will compete head-to-head with frontier AI labs and hyperscalers for candidates who are often managing multiple highly competitive offers. Winning in this market requires deep technical literacy, exceptional speed, and continuous market intelligence.</p>
<p><b>
This isn't for everyone.</b> But if you want to work on an elite team to hire the most sought-after talent in frontier AI and help build the teams defining what comes next in the field, this role may be for you!</p>
<h3 class="jobSectionHeader"><b>
What You'll Do</b></h3>
<h4 class="jobSectionHeader"><b>Sourcing &amp; Pipeline Building</b></h4>
<ul><li>Look beyond standard keyword searches by continuously tracking arXiv preprints, GitHub activity, OpenReview submissions, and open-source contributions.</li>
<li>Map and cultivate passive talent ecosystems across top PhD programs (Stanford, MIT, CMU), frontier research labs and high-growth AI startups.</li>
<li>Build proactive candidate pipelines long before formal requisitions open, using emerging signals across research, open-source, and professional networks to identify and engage exceptional talent early.</li>
</ul><h4 class="jobSectionHeader"><b>Engaging Incredibly Hard-to-Reach Talent</b></h4>
<ul><li>Reach passive researchers, Research Engineers, and Forward-Deployed Engineers who do not respond to generic recruiter outreach.</li>
<li>Demonstrate the technical fluency to assess candidate relevance, understand research contributions, and partner with technical leaders on candidate calibration across relevant technical domains.</li>
</ul><h4 class="jobSectionHeader"><b>Closing Highly Sought-After Talent</b></h4>
<ul><li>Partner directly with the CEO, CTO, and research leaders to design and execute individualized closing playbooks for highly sought-after talent.</li>
<li>Win contested offers by understanding each candidate's motivations and leveraging the aspects of the opportunity that matter most to them.</li>
</ul><h3 class="jobSectionHeader"><b>What We're Looking For</b></h3>
<ul>
<li><p><b>Technical Recruiting Track Record</b>: 4+ years of full-lifecycle <b>technical recruiting </b>experience, with <b>proven depth</b> in AI/ML, Research Engineering, Distributed Systems, or Forward-Deployed Engineering.</p>
</li>
<li><p><b>Domain Literacy</b>: Ability to speak credibly with top researchers and technical leaders.</p>
</li>
<li><p><b>Proven Closer</b>: Demonstrated track record of personally sourcing and closing highly sought-after candidates against competing offers from frontier labs or hyperscalers.</p>
</li>
<li><p><b>Compensation &amp; Equity Fluency</b>: Strong understanding of private-company equity, technical compensation, and competitive market benchmarking.</p>
</li>
<li><p><b>High Ownership &amp; Startup Speed</b>: Ability to operate with high urgency in a fast-moving AI research environment.</p>
</li>
</ul><h3 class="jobSectionHeader"><b>What Success Looks Like</b></h3>
<ul><li><b>Compounding Talent Density</b>: Continuously raising the technical caliber and execution velocity of Turing's Research Engineering and Forward-Deployed AI teams.</li>
<li><b>High Win Rates</b>: Consistently converting highly sought-after candidates and maintaining strong offer acceptance rates in contested searches.</li>
<li><b>Trusted Technical Partnership</b>: Earning deep trust with research directors and technical leads, acting as an embedded advisor who understands the research roadmap.</li></ul><p></p><div><h2 class="jobSectionHeader"><b><br>
Values</b></h2>
<ul><li><b>We are client first:</b> We put our clients at the center of everything we do, because their success is the ultimate measure of our value.<br>
</li>
<li><b>We work at Start-Up Speed:</b> We move fast, stay agile and favor action because momentum is the foundation of perfection<br>
</li>
<li><b>We are AI forward:</b> We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.</li>
</ul><h2 class="jobSectionHeader"><b>Advantages of joining Turing</b></h2>
<ul><li><b>Work at the frontier of AI</b>, helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.<br>
</li>
<li><b>Contribute to leading-edge AI research</b> and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.<br>
</li>
<li><b>Bring frontier AI innovation to the enterprise</b>, applying lessons learned from leading AI labs to solve real-world business challenges.<br>
</li>
<li><b>Collaborate with and learn from exceptional colleagues</b> with deep AI experience from Google, Meta, Amazon, and other leading technology companies.<br>
</li>
<li><b>Move at the pace of AI innovation</b>, with the speed, ownership, and impact of a startup.</li></ul><br>
<p></p>
<p>
Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.</p>
<div>
<p>For applicants from the European Union, please review Turing's GDPR notice here.</p></div></div></div><p></p>

Senior Technical Recruiter - Research Engineering Pod

Explore 2+ Artificial intelligence specialist in Seattle this September. Find roles across top companies and apply now to boost your career.

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Agentic AI Engineer — Healthcare AI

Senior Technical Recruiter - Research Engineering Pod