Deloitte seeks an Agentic AI Engineer to design and deploy agentic systems powered by large language models and related technologies for healthcare decisioning, delivering end-to-end architecture from development to production in real-world clinical and operational settings.

Location: Jacksonville, FL (onsite)

Responsibilities

Architect and deliver agentic systems that perform multi-step reasoning, planning, tool use, and workflow orchestration within complex, regulated operations.
Develop persistent workflows with LangGraph and LangChain (or equivalents), incorporating branching, retries, self-correction, human-in-the-loop checkpoints, and reusable orchestration patterns.
Design for long-horizon reliability, ensuring multi-step task completion, recovery from cascading errors, planning under uncertainty, and robust tool use when individual steps fail.
Frame regulated decision making with policy- and criteria-grounded outputs, structured proposer/critic/judge style reviews, and auditable rationales for high stakes decisions across clinical review, prior authorization, claims integrity, and care management.
Build end-to-end Retrieval-Augmented Generation pipelines, covering ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, contextual compression, and grounding strategies.
Engineer memory and context management, including conversational state, persistent memory, retrieval-informed context assembly, and token-efficient context selection.
Apply contemporary context-delivery patterns so agents access the right information at the right time using tool and context interfaces.
Establish observability and tracing for prompts, tool calls, retrieval quality, agent traces, failures, drift, latency, and production behavior.
Implement guardrails and safety controls with robust failure handling to minimize hallucinations and unsafe actions.
Evaluate agents at trajectory and task levels, including multi-step task success, failure modes, regression analysis, sandboxed tests, and accompanying retrieval and generation quality metrics, automated checks, and human review.
Engineer healthcare-grade safety with deployment eval gates, human oversight and escalation models, auditable traceability for regulated decisions, and PHI/HIPAA-aware data handling.
Integrate with internal and external tools, APIs, enterprise systems, databases, and model providers to ensure safe operation within real business workflows.
Deliver production-quality code with solid testing, CI/CD, logging, versioning, and documentation; make architecture decisions balancing quality, safety, latency, cost, and model risk.
Collaborate with modeling and post-training engineers to improve tool use, grounding, and long-horizon reasoning through evaluation-driven feedback and, where helpful, fine-tuned or reasoning-optimized models.
Translate ambiguous, high-complexity processes into robust system logic and reusable AI patterns; stay current with agentic-system advances and translate research into practical engineering decisions.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, Computational Linguistics, or a related field.
Proven track record delivering production-grade agentic systems; this is core expertise with a history of shipped systems, research releases, or open-source contributions, plus strong software and ML fundamentals and hands-on agentic work.
Extensive hands-on experience building production agent systems with modern orchestration frameworks such as LangGraph and LangChain (or equivalents), including custom orchestration.
Experience designing and optimizing end-to-end RAG pipelines: indexing, retrieval, reranking, grounding, and evaluation.
Deep understanding of memory and context management, including context windows, retrieval-driven context assembly, persistent memory, and high-signal context selection.
Solid, practical grasp of LLM behavior, including strengths, limitations, hallucination risks, reasoning constraints, and latency/cost trade-offs, plus associated evaluation methods.
Experience evaluating and debugging agent behavior with task-success and trajectory analysis, beyond output quality.
Strong Python engineering skills and modern software practices: testing, CI/CD, version control, API integration; experience implementing observability, tracing, and debugging for production LLM-based systems.
Hands-on experience with at least one frontier model platform (Anthropic, Google, OpenAI) and/or open-weight/self-hosted models (e.g., Llama via vLLM), including production tool use and agent capabilities.
Ability to travel up to 50 percent of the time depending on projects and client needs.
Limited immigration sponsorship may be available.

Technologies

LangGraph, LangChain
Retrieval-Augmented Generation (RAG)
Python
vLLM, Llama
Anthropic, Google, OpenAI
Pinecone, Weaviate, Milvus

The Team

Deloitte combines AI researchers, modeling and platform engineers, architects, clinical and domain specialists, and product leaders to build vertical AI systems. The healthcare focus spans payers, providers, and life sciences, tackling complex reasoning problems, nuanced workflows, and a rigorous operating environment.

Preferred Qualifications

Experience with multi-agent systems and agent collaboration patterns.
Familiarity with vector databases and retrieval infrastructure such as Pinecone, Weaviate, or Milvus.
Exposure to model adaptation and fine-tuning techniques such as LoRA or QLoRA.
Foundational NLP knowledge: tokenization, semantic similarity, entity extraction, summarization, and transformer concepts.
Experience operating in highly regulated, high-stakes, or complex environments; healthcare exposure or standards like FHIR is a plus, not required.
Proven habit of staying current with AI research, benchmarks, and emerging engineering patterns.

Compensation

The estimated base salary range is $110,700–$372,900 per year, not adjusted for geographic differential. Actual base pay depends on skills, experience, and level. The role includes a substantial performance-based incentive opportunity tied to value delivered.

Agentic AI Engineer — Healthcare AI