Agentic AI Engineer - RAG Architecture - LLM Systems

Build the Future with AspenView Technology Partners

At AspenView, we are passionate about transforming the way organizations approach technology. We specialize in creating high-performing, nearshore IT teams to help North American clients innovate faster and more efficiently.

As we continue to grow, we’re looking for exceptional people to join our team and help drive impactful change across industries.

Role Overview
We are seeking a high-caliber Agentic AI Engineer specializing in RAG (Retrieval-
Augmented Generation) and Large Language Models (LLMs) to design, build, and deploy
production-grade autonomous AI systems.
In this role, you will lead the architecture and implementation of multi-step agentic workflows
capable of reasoning, tool execution, and synthesizing complex clinical and operational data.
You will engineer sophisticated RAG pipelines that bridge unstructured medical knowledge with
enterprise EHR systems, establishing strict safety guardrails, hallucination controls, and HIPAA-
compliant AI pipelines.

Key Responsibilities
● Agentic System Engineering: Architect and deploy autonomous agentic AI workflows
and multi-agent systems (using frameworks like LangGraph, LlamaIndex, AutoGen, or
CrewAI) capable of multi-step reasoning, dynamic tool usage, and clinical task
execution.
● Advanced RAG Architecture: Design, optimize, and scale production RAG pipelines
utilizing hybrid search (dense + sparse retrieval), re-ranking, query transformation,
context compression, and semantic routing over multi-modal clinical and research
datasets.
● LLM Fine-Tuning & Evaluation: Evaluate, fine-tune, and benchmark foundational
models (e.g., Llama 3, Claude, GPT-4, Med-PaLM) for specialized healthcare tasks,
establishing rigorous evaluation frameworks (e.g., Ragas, TruLens) for accuracy,
groundness, and latency.
● Vector Database Infrastructure: Manage and optimize vector stores (Pinecone,
Qdrant, Milvus, Weaviate, or pgvector) for high-concurrency, low-latency similarity
searches and knowledge retrieval.
● Guardrails & HIPAA Compliance: Implement enterprise safety controls, input/output
sanitization, and hallucination guardrails (e.g., NeMo Guardrails, Llama Guard) to ensure
100% HIPAA compliance and zero unauthorized PHI leakage.
● Cross-Functional Innovation: Collaborate closely with US-based clinical researchers,
cloud architects, and product leads to translate complex healthcare needs into
autonomous AI capabilities.

Required Technical Skills
● AI Software Engineering Experience: 4+ years in software production engineering,
with at least 2+ years dedicated to building LLM applications, Agentic workflows, and
RAG architectures in production.
● Agentic Frameworks & Orchestration: Strong mastery of modern AI orchestration
ecosystems (LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI).
● Search & Retrieval Infrastructure: Deep knowledge of Vector Databases (Pinecone,
Qdrant, Milvus, pgvector), embedding models, semantic chunking strategies, and re-
ranking models (e.g., Cohere Rerank, BGE).
● Programming & Cloud AI Stack: Advanced proficiency in Python, with hands-on
deployment experience on cloud platforms (AWS Bedrock / SageMaker or Azure
OpenAI / Vertex AI).
● Model Evaluation & Guardrails: Experience implementing LLM observability,
evaluation metrics (faithfulness, answer relevance), and safety frameworks.
● Healthcare Interoperability (Preferred): Familiarity with medical ontologies (SNOMED,
LOINC, ICD-10) and healthcare data interfaces (FHIR APIs, HL7) is a strong plus.
● Language Proficiency: Advanced/Fluent English (C1/C2) for daily technical
collaboration with Boston-based technology and research leadership.

Soft Skills & Competencies
● Systems Thinking for Non-Deterministic AI: Exceptional ability to debug, evaluate,
and stabilize non-deterministic model outputs for mission-critical healthcare applications.
● Clinical & User Empathy: Deep commitment to designing transparent, explainable, and
safe AI systems that empower clinicians rather than replace them.
● Proactive nearshore Ownership: Self-starter capable of driving end-to-end AI features
autonomously in a remote-first, agile nearshore setting.
● Clear Technical Storytelling: Ability to communicate complex AI concepts,
architectural trade-offs, and evaluation metrics clearly to non-technical stakeholders.

Visa Sponsorship

AspenView does not sponsor employment visas for this role. Applicants must be currently authorized to work in the United States on a permanent basis without the need for visa sponsorship now or in the future.

Equal Opportunity Employer

AspenView is proud to be an equal opportunity employer. We believe in creating an environment where all employees feel welcome, valued, and empowered to succeed. We celebrate diversity and strive to build a culture of inclusion where all individuals, regardless of their race, color, gender, gender identity or expression, sexual orientation, disability, age, or any other characteristic, can thrive. We encourage applicants from all walks of life to join our team and make a lasting impact.