Agentic AI / Machine Learning Consultant

Vertical Relevance; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Vertical Relevance is seeking an Agentic AI/Machine Learning Consultant to lead end-to-end ML/AI design, development, and deployment for clients in the NY Metro area. You will collaborate with cross-functional teams to implement technical solutions and ensure client success, with a focus on cloud-native architectures and secure data handling.

You will design AI/ML pipelines, build knowledge graphs, and optimize retrieval systems using AWS/GCP services, SageMaker, Bedrock, and OpenSearch, while

Qualifications

• Experience building and deploying ML/AI solutions in AWS, GCP, or Azure.
• Strong expertise in RAG systems and retrieval optimization.
• Experience with vector databases and hybrid search techniques.
• Knowledge of knowledge graphs and entity resolution.
• Proficiency in Python (R is a plus).
• Experience with LLM platforms such as OpenAI, Anthropic, or Gemini.
• Strong communication and client-facing skills.

Responsibilities

• Deliver end-to-end ML/AI solutions from problem framing through deployment and monitoring.
• Design scalable AI/ML architectures using AWS and GCP services.
• Optimize RAG pipelines including chunking, embeddings, hybrid search, and re-ranking.
• Develop retrieval evaluation frameworks (Recall@K, Precision@K, MRR, nDCG).
• Design and implement knowledge graphs and ontologies.
• Build data ingestion pipelines for structured and unstructured data.
• Deploy solutions using AWS tools such as SageMaker, Bedrock, Lambda, and OpenSearch.
• Implement self-hosted embedding models in secure environments.
• Ensure compliance with PHI/PII data security requirements.
• Collaborate with cross-functional teams and act as a technical advisor.
• Mentor team members and contribute to technical thought leadership.

Skills

Cloud platforms (AWS/GCP/Azure)

RAG systems & retrieval optimization

Vector databases & hybrid search

Knowledge graphs & entity resolution

Python

LLM platforms (OpenAI, Anthropic, or/`

Tools

SageMaker

Bedrock

OpenSearch

Lambda

Amazon Neptune

Job description

Vertical Relevance is seeking an Agentic AI/ Machine Learning Consultant to join our team. In this role, you will be responsible for the end-to-end design, development, and deployment of advanced ML/AI solutions. You’ll work closely with clients to deliver impactful outcomes, leveraging Cloud services and cutting‑edge technologies in the Hybrid in NY Metro Area.

As an Agentic AI/Machine Learning Consultant, you will collaborate with cross‑functional teams to implement technical solutions that solve complex business challenges. This position requires strong technical expertise, excellent communication skills, and a passion for driving customer success.

At Vertical Relevance, we believe in teamwork, automation, continuous learning, and ownership. If you’re ready to innovate and make a measurable impact, we’d love to hear from you!

Key Responsibilities

• Deliver end-to-end ML/AI solutions from problem framing through deployment and monitoring
• Design scalable AI/ML architectures using AWS and GCP services
• OptimizeRAG pipelines including chunking, embeddings, hybrid search, and re‑ranking
• Develop retrieval evaluation frameworks (Recall@K,Precision@K, MRR,nDCG)
• Design and implement knowledge graphs and ontologies
• Build data ingestion pipelines for structured and unstructured data
• Deploy solutions using AWS tools such as SageMaker, Bedrock, Lambda, and OpenSearch
• Implement self-hosted embedding models in secure environments
• Ensure compliance with PHI/PII data security requirements
• Collaborate with cross‑functional teams and act as a technical advisor
• Mentor team members and contribute to technical thought leadership

Required Qualifications

• Experience building and deploying ML/AI solutions in AWS, GCP, or Azure
• Strongexpertisein RAG systems and retrieval optimization
• Experience with vector databases and hybrid search techniques
• Knowledge of knowledge graph design and entity resolution
• Proficiencyin Python (R is a plus)
• Experience with LLM platforms such as OpenAI, Anthropic, or Gemini
• Strong communicationand client-facing skills

Preferred Qualifications

• Experience with Amazon Neptune or other graph databases
• Familiarity with information retrieval metrics
• Experience with self-hosted embeddings
• Healthcare domain knowledge (payer/claims)
• Experience with agentic AI frameworks such asLangGraphor MCP

About Vertical Relevance

Vertical Relevance was founded to help business leaders drive value through the design and delivery of effective transformation programs across people, processes, and systems. Our mission is to help firms at any stage of their journey develop custom solutions for success and growth. We provide a full range of services from strategy and design through to implementation and training. Our collective industry expertise is our greatest asset - our professionals have an average of 20+ years’ experience within Financial Services, across Wealth Management, Asset Management, Insurance, and Banking. Within our Customer Experience practice, we add complementary industry expertise (technology and media) synergizing the most relevant and successful customer trends. We focus wholly on your success by first rigorously assessing your business and technology challenges, and then right-sizing solutions that provide a meaningful ROI. With our industry experts hitting the ground running and focusing on nimble, quality delivery, we can see rapid, tangible improvements with our clients in productivity and effectiveness. When it makes sense for your company, we leverage our product partnerships in the areas of CRM, Sales Acceleration, Predictive Analytics, Digital Knowledge Management, and Cloud Transformation.

Vertical Relevance is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.