Gen AI Engineer

Job Title

Gen AI Engineer

Location

New York, NY

Duration

6 months (Extendable)

Pay Range

$85-90/Hour on W2/C2C (All Inclusive)

Request ID

115387-1

This is a hands-on, full-stack AI role

you design, build, and deliver AI solutions end to end, across traditional ML, Generative AI, and Agentic AI, while shaping technical strategy and mentoring/managing a growing team.

As a Principal AI Engineer in the Artificial Intelligence & Data (AI&D) organization, you will be a senior technical leader driving AI transformation.

This is a hands-on, full-stack AI role

you design, build, and deliver AI solutions end to end, across traditional ML, Generative AI, and Agentic AI, while shaping technical strategy and mentoring/managing a growing team.

You will scope and deliver core AI solutions in close partnership with business stakeholders, data scientists, engineers, and product and technology partners, and help shape enterprise AI practices and standards, bringing deep expertise in AI solution delivery,

responsible AI principles, You will own solution delivery on top of the enterprise AI platform, shipping agentic solutions end to end rather than building the underlying platform infrastructure. Additionally, you will partner with the business to assess and quantify the overall value delivered by the AI solution.

What You’ll Do

• Lead AI/ML and GenAI initiatives end-to-end, in partnership with data, technology,

product, and business teams. Scope and shape initiatives from opportunity

identification and feasibility assessment through solution design, delivery, and

stakeholder alignment.

• Own end-to-end delivery for AI solutions, from build through evaluation, deployment,

and production monitoring, shipping and operating them on the enterprise AI platform

using its existing CI/CD, IaC templates, and gateway.

• Design and implement agentic AI systems, including multi-agent orchestration, tool

use, memory architectures, human-in-the-loop checkpoints, and safety guardrails.

Build multi-agent solutions with sub-agents that plan, implement, validate, deploy, and

log.

• Design and deploy production-grade RAG and retrieval systems, including hybrid

search, reranking, evaluation, and advanced retrieval patterns (agentic RAG, graphenhanced retrieval) as appropriate.

Lead technical decisions across the AI stack

model selection, orchestration

frameworks and tool-integration protocols (e.g., LangGraph, MCP, or direct API

integration), cloud AI platforms (GCP, AWS), and data platform (Databricks) integration.

• Rapidly prototype AI-powered applications and interfaces to validate ideas, test

usability, and accelerate adoption, using modern frameworks (Streamlit, React, or

similar).

• Build with AI-assisted engineering tools daily (such as Codex, Claude Code) as a force

multiplier, with critical review of all generated output. Build engineering agents that

accelerate the team's own delivery, for example agents that assist with testing, code

review, or deployment validation, not just use AI tools to write code.

• Define and evolve technical standards for AI development, including evaluation

frameworks, testing practices, observability, and responsible AI principles. Evaluate

and integrate emerging AI capabilities (new foundation models, agent frameworks, AIassisted development tools).

• Provide technical leadership and mentorship to data scientists and AI engineers,

fostering a culture of rapid experimentation, rigorous evaluation, and continuous

learning.

• This role involves limited travel (<10%) to events and vendor meetings.

What You’ll Bring

• Advanced degree (MS or PhD) in Computer Science, AI, Engineering, Mathematics, or a

related quantitative field.

• 8+ years of experience applying data science, ML, and AI to real-world business

problems, with progressive growth in scope, complexity, and influence.

• Fluent with AI-assisted engineering tools, such as Codex, Claude Code, used daily as a

force multiplier, with critical review of generated output. Experience building

engineering agents that accelerate delivery itself, such as testing, code review, or

deployment-validation agents, not just using AI tools to write code.

Full-stack AI fluency

demonstrated ability to work across the spectrum from statistical

modeling and ML to LLM application development and agentic system design, including

rapid prototyping (e.g., Streamlit, React) and owning solutions through to production.

• Strong software engineering skills in Python; working knowledge of SQL and

JavaScript/TypeScript sufficient to build and ship a solution's front end (e.g., React).

Comfort with modern development practices including testing, code review, and CI/CD.

Working fluency with containers (Docker) and Kubernetes-based deployment, sufficient

to independently ship and operate a solution on the platform, not to build or own

platform infrastructure.

• Deep hands-on experience with LLMs, RAG architectures, and prompt engineering,

including graph-based retrieval (GraphRAG, knowledge graphs) alongside traditional

vector-based RAG. Hands-on experience with multi-agent and sub-agent orchestration

frameworks (e.g., LangGraph, Google ADK, or equivalent) and MCP or equivalent toolintegration protocols, for production agentic systems.

Experience developing and evaluating AI systems rigorously

automated evaluation

pipelines, red-teaming, hallucination detection, safety testing, and performance

monitoring.

• Proficiency with cloud AI platforms, particularly GCP Vertex AI for agentic development,

with working knowledge of AWS services (SageMaker, Bedrock) and modern data

platforms (Databricks). Comfort consuming cloud-native platform services (existing IaC

templates, CI/CD pipelines, the AI gateway) to deploy and operate solutions.

Strong stakeholder engagement and communication skills

ability to scope initiatives,

present to senior leaders, manage expectations, and drive alignment across business

and technology partners.

• Track record of mentoring and elevating technical talent.
• Experience in life insurance, financial services, or other regulated industries is a plus.

Success Looks Like

• Agentic solutions live in production, delivering measurable business value across value

streams.

• Trusted partnership with business stakeholders, from scoping through delivery and

adoption.

• Reusable solution patterns that other teams can build on.
• A rising bar for technical rigor and AI-assisted delivery across the team

Desirable Skills

Keyword

Skills

AI & Gen AI - Products & Tools

Experience Required

10 & Above