Lead AI Engineer

Blend360; New York (NY); On-site; USD 108,000 - 180,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401K

Paid time off

Commuter benefits

Life insurance

Disability coverage

Employee assistance programs

Paid holidays

Job summary

Blend360 is seeking a Data Scientist – Applied AI & Prompt Engineering to design, build, and deploy LLM-powered solutions that directly impact products and users. You will work hands-on with LLMs, transformers, and RAG in collaboration with Engineering to move prototypes to production.

You will design prompts, workflows, and multi-step agentic systems, deploy GenAI pipelines in cloud environments, and build evaluation frameworks to measure grounding, latency, and cost.

Qualifications

• 3+ years applied ML with focus on NLP or generative AI systems.

Responsibilities

• Architect and implement production-ready AI solutions with LLMs and transformers.

Skills

Applied ML

NLP

Transformers

Python

LangChain

APIs

Experimentation

Production code

Guardrails

Agentic systems

Education

Degree in CS/Data Science/Engineering

Tools

LangChain

LlamaIndex

OpenAI API

CrewAI

Azure Promptflow

AWS Bedrock

Job description

Company Description

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning humanexpertisewith artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-drivenstrategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

Job Description

We’regrowing our Data Science team to drive innovation in Generative AI. As a Data Scientist – Applied AI & Prompt Engineering, you will design, build, and deploy LLM-powered solutions that directlyimpactour products and users.You’llwork hands-on with LLMs, transformers, retrieval-augmented generation (RAG), and AI agents, collaborating with Engineering to bring prototypes all the way to productionand take ownership of their ongoing maintenance, enhancement, and evolution.

What You’ll Do

• Architect and implement production-ready AI solutions involving LLMs, transformer-based models, retrieval systems, agentic workflows, and AI agents for generative tasks and automation.
• Design and iterate on prompts, workflows, and RAG pipelines to improve accuracy, cost-efficiency, latency, and safety.
• Design and build multi-step agentic systems that break down complex tasks, invoke external tools or APIs, manage state, and handle reasoning chains robustly.
• Deploy models and GenAI pipelines in production environments (API, batch, streaming), ensuring reliability and scalability.
• Build and maintain evaluation frameworks to measure model grounding, factuality, latency, and cost.
• Develop and integrate guardrails (e.g., prompt-injection protections, content moderation, output validation), and safeguards for agent loops (e.g., loop prevention, tool call limits, state validation).
• Collaborate cross-functionally with Product, Engineering, and ML Ops to deliver high-quality AI features end-to-end.

Qualifications

3+yearsapplied machine learning, with hands-on focus on NLP, transformers, or generative AI systems.

LLMand AgentTools:Hands-on experience with LLM-related libraries(e.g.LangChain,LlamaIndex, OpenAI API,CrewAI,or similar)and services(Azure Promptflow, AWS Bedrock agents, or similar)

AgenticSystems:Experience designingmulti-step agentsthat combine LLM reasoning with tool/API calls, with safeguards against errors, loops, and unsafe tool use.

ML Foundations:Proven experience building and deploying machine learning models to production (API, batch, or streaming).

Coding:Fluency in Python, with clean, modular, production-grade code practices.

Experimentation:Strong ability to design and analyze ML experiments; track performance using metrics, not gut feel.

Deployment:Ability to develop, deploy andmonitorAI-poweredapplicationsin cloud environments(e.g.AWS, Azure, GCP) using APIs, batch, or streaming architectures. Familiarity with containerization, versioning, and CI/CD.

Responsible AI:Experience implementing privacy, bias mitigation, safety guardrails, or related practices.

Additional Qualifications

• Degree in Computer Science, Data Science, Engineering, ora relatedfield (or equivalent experience).
• Expertise intransformer-based models and LLM architectures.
• Ability to bridge rapid prototyping and production deployment — you own what you build through to live systems.
• Strong collaborator who thrives at the intersection of DS + Engineering.

Additional Information

The starting pay range for this role is $125,000 - $180,000. Actual compensation within the range will be dependent on several factors including but not limited to relevant experience, skills, certifications, training, and location. It is not typical for an individual to be hired at or near the top of the range and determining factors for compensation are considered for each individual circumstance. BLEND360 also offers a competitive benefits program to meet the health and financial well-being of our team and their families. You can look forward to a range of benefits including medical, dental, vision, 401K, PTO, paid holidays, commuter benefits, spending accounts, life insurance, disability coverage, and EAPs.