Technical Architect - Machine Learning - (New Jersey Location)

Quantiphi; New Jersey; On-site; USD 140,000 - 190,000; Full time

Job summary

Quantiphi is seeking a Technical Architect - ML to design enterprise-scale AI and GenAI solutions. You will lead multi-agent architectures, evaluate models and tools, and drive engineering standards across delivery teams.

Required hands-on experience with LangGraph, LangChain, vector databases, and RAG-based retrieval. Relocation to New Jersey is expected, with a focus on scalable, production-grade AI systems.

Qualifications

• Experience designing production-scale AI and GenAI systems.
• Deep understanding of agent orchestration patterns.
• Experience with RAG, hybrid retrieval and reranking.
• Knowledge of LoRA/PEFT and model customization.
• Strong RL concepts and application to agentic systems.

Responsibilities

• Design enterprise-scale AI and GenAI solutions.
• Lead evaluation of models, vector databases, and tooling.
• Define multi-agent orchestration patterns and tooling integration.
• Enforce engineering standards for observability and testing.
• Mentor delivery teams through architectural guidance.
• Conduct architecture reviews and code reviews across teams.
• Collaborate with stakeholders to translate requirements into scalable solutions.
• Contribute to proofs of concept and validation activities.

Skills

AI Solution Design

Agent Architecture

Retrieval Architecture

Fine-Tuning

Reinforcement Learning

Technology Evaluation

Engineering Leadership

AI Engineering Ecosystem

Cloud Platforms

Telecom Solutions

Tools

LangGraph

LangChain

MCP

Vector Databases

Evaluation Frameworks

Job description

is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations. Since our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology’s sake. Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact.

Role: Technical Architect - ML – Machine Learning (ML)

Ready to relocate (New Jersey Location)

Responsibilities

• Design and lead the implementation of enterprise-scale AI, Generative AI, RAG, and Agentic AI solutions.
• Lead the evaluation and selection of foundation models, vector databases, embedding models, agent frameworks, retrieval strategies,, and supporting technologies based on functional and non-functional requirements.
• Design multi-agent systems, orchestration workflows, tool integration patterns, and evaluation frameworks
• Define and enforce engineering standards within delivery teams covering observability, evaluation, testing, and deployment practices.
• Guide engineering teams through technical design, development, testing, deployment, and operationalization activities.
• Conduct architecture reviews, code reviews, and technical mentoring across engineering teams.
• Collaborate with business stakeholders, architects, and delivery teams to translate requirements into scalable technical solutions.
• Contribute to critical implementations, proofs of concept, and architecture validation activities.

Experience - 10 +

Must-Have Skills

• AI Solution Design - Experience designing production-scale AI and GenAI systems, not just implementing them.
• Agent Architecture - Deep understanding of agent orchestration patterns, multi-agent systems, and tool integration approaches.
• Retrieval Architecture - Experience designing RAG, hybrid retrieval, reranking, and retrieval optimization strategies.
• Fine-Tuning - LoRA, PEFT, model customization, and adaptation techniques.
• Reinforcement Learning - Solid understanding of RL concepts and application in agentic Systems.
• Technology Evaluation - Ability to evaluate models, frameworks, vector databases, and AI tooling based on business and technical requirements.
• Engineering Leadership - Drive engineering excellence and technical ownership within delivery teams through rigorous code/design reviews, structured mentoring, and architectural guidance.
• AI Engineering Ecosystem - Strong hands-on expertise across LangGraph, LangChain, MCP, vector databases, and evaluation frameworks.
• Cloud Platforms - Experience designing and deploying AI solutions on GCP and/or Azure. Good-to-Have Skills Telecom Solutions -
• Experience working in telecom industry Knowledge graph integration Experience designing GraphRAG or hybrid retrieval architectures combining vector search with graph-based knowledge retrieval. MLOps / LLMOps Model lifecycle management, observability, and production AI operations.