Onsitefull timeReq 26-02633Posted Today

Principal GenAI Engineer

Direct Placement role in NYC, NY. Onsite engagement, matched and submitted by an ApTask vertical recruiter.

Location: NYC, NY · Onsite
Compensation: $160k–$200k/yr

Your résumé routes to the vertical recruiter who owns this requisition. Identity-verified profile, never resold or syndicated.

Stack

GenAI

About the role

Pay transparency disclosures

Required information for this posting

Applies to: New York

Compensation: Anticipated pay range for this role: $160,000–$200,000 per year. Where you land within the range depends on validated experience, the depth of the stack match, and — for contract engagements — the bill rate the client has locked in for this requisition.
Other compensation: No additional bonuses, commissions, tips, or piece-rate compensation are anticipated for this role beyond the pay range above, unless specifically noted in the description. Any additional compensation would be described in your written offer letter.
New York City and Westchester applicants: If this role is or may be performed in New York City, Westchester County, or Ithaca, additional local pay-disclosure ordinances apply. The pay range shown above is intended to comply with those ordinances as well.

This posting is intended to comply with the pay transparency disclosure requirements of the state(s) listed above — N.Y. Lab. Law § 194-b. If any information here appears inconsistent with the description below, this disclosure block controls — it is the authoritative statement of pay and benefits for this posting.

Title: Principal GenAI Engineer

Principal GenAI Engineer with strong expertise in LLMs to lead enterprise-scale AI implementations for Fortune 500 clients.
This role focuses on building RAG systems that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, explainable, production-grade AI solutions.

What We re Looking For

8-13 years of experience in ML/AI systems
2 years hands-on experience with LLMs (RAG, agents, prompt engineering)
Strong proficiency in Python, LangGraph, and SQL
Experience deploying GenAI systems on AWS / Azure / GCP

Roles & Responsibilities

Develop and optimize LLM-based solutions: Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
Codebase ownership: Build and maintain/review high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

About technology at ApTask

What this vertical looks like inside ApTask.

Technology roles at ApTask cover the software, cloud, data, security, and platform-engineering functions that power Fortune 500 digital operations. Our recruiters specialise in high-signal technical calibration — every candidate is validated against the specific stack, framework versions, and deployment context the client runs, not a keyword match. Our largest engagements sit inside AWS, Azure, GCP, Snowflake, Databricks, and modern data-mesh estates. Because we route through Fieldglass, Beeline, Workday VNDLY, and Coupa VMS, technology contractors placed through ApTask carry MBE diversity spend against the client's supplier program while remaining W-2 with full benefits under our payroll.

How it works

What happens after you apply.

1. Verified profile
Submit your résumé and complete the ApTask identity + skills verification. We check right-to-work, background, and technical calibration once — never resell or re-verify — so future roles surface faster.
2. Recruiter calibration call
Within one business day, the recruiter who owns this requisition reviews your profile against the client's specific stack, arrangement, and start-date requirements. You'll hear back either way — no ghosting.
3. Client interview
If your profile is a fit, we present you to the hiring team. Most clients run 2-3 interview stages: hiring-manager screen, technical panel, and final. We prep you with the exact scorecard criteria before each round.
4. Offer + onboarding
On acceptance, you onboard W-2 with ApTask (contract) or direct-hire with the client (per role type). Benefits, payroll, and timesheets run through us. Your recruiter stays your point of contact for the length of the engagement.

Frequently asked

Questions candidates ask about this role.

Is the Principal GenAI Engineer role on-site?: Yes — this role is on-site at the client's NYC, NY location, five days per week. The client's culture and delivery cadence are calibrated around in-person collaboration for this position. Relocation support may be available for the right candidate; the recruiter will confirm during your calibration call.
Is this a permanent role?: Yes — this is a full time direct-hire position with the client. On offer acceptance, you onboard directly onto the client's payroll and benefits. ApTask's role is placement only; the recruiter stays in touch for the first 90 days as a check-in, but your day-to-day relationship is with the client's hiring manager.
What is the compensation range for this role?: The advertised range for this Principal GenAI Engineer role is $160,000–$200,000 per year. Where you land within the band depends on validated experience, the specific stack calibration match, and — for contract engagements — the bill-rate the client has locked in for this requisition. The recruiter will discuss the exact number during your calibration call.
How quickly does the interview process move?: If your profile is a fit for this role, you can expect the recruiter's first call within one business day. From there, interview cadence depends on the client's hiring-manager and panel availability. Total time from submission to signed offer varies by client — pre-verified profiles and calibrated submissions cut the noise, but the pace of interviews is driven by the client, not us.
What technical skills does the Principal GenAI Engineer role require?: The client is targeting depth in GenAI. Adjacent experience is welcome — we routinely place candidates whose exact stack match is 60-70% when the underlying pattern (distributed systems, regulated-data handling, or comparable) is strong. Bring the full stack breadth to your calibration call; the recruiter will map it onto the client's evaluation scorecard.

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Principal GenAI Engineer

Direct Placement role in NYC, NY. Onsite engagement, matched and submitted by an ApTask vertical recruiter.

Location: NYC, NY · Onsite
Compensation: $160k–$200k/yr

Talk to a recruiter

Your résumé routes to the vertical recruiter who owns this requisition. Identity-verified profile, never resold or syndicated.

Stack

GenAI

About the role

Pay transparency disclosures

Required information for this posting

Applies to: New York

Compensation: Anticipated pay range for this role: $160,000–$200,000 per year. Where you land within the range depends on validated experience, the depth of the stack match, and — for contract engagements — the bill rate the client has locked in for this requisition.
Other compensation: No additional bonuses, commissions, tips, or piece-rate compensation are anticipated for this role beyond the pay range above, unless specifically noted in the description. Any additional compensation would be described in your written offer letter.
New York City and Westchester applicants: If this role is or may be performed in New York City, Westchester County, or Ithaca, additional local pay-disclosure ordinances apply. The pay range shown above is intended to comply with those ordinances as well.

8-13 years of experience in ML/AI systems
2 years hands-on experience with LLMs (RAG, agents, prompt engineering)
Strong proficiency in Python, LangGraph, and SQL
Experience deploying GenAI systems on AWS / Azure / GCP

Roles & Responsibilities

Develop and optimize LLM-based solutions: Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
Codebase ownership: Build and maintain/review high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.

What this vertical looks like inside ApTask.

What happens after you apply.

1. Verified profile

Submit your résumé and complete the ApTask identity + skills verification. We check right-to-work, background, and technical calibration once — never resell or re-verify — so future roles surface faster.

2. Recruiter calibration call

Within one business day, the recruiter who owns this requisition reviews your profile against the client's specific stack, arrangement, and start-date requirements. You'll hear back either way — no ghosting.

3. Client interview

If your profile is a fit, we present you to the hiring team. Most clients run 2-3 interview stages: hiring-manager screen, technical panel, and final. We prep you with the exact scorecard criteria before each round.

4. Offer + onboarding

On acceptance, you onboard W-2 with ApTask (contract) or direct-hire with the client (per role type). Benefits, payroll, and timesheets run through us. Your recruiter stays your point of contact for the length of the engagement.

Questions candidates ask about this role.

Is the Principal GenAI Engineer role on-site?

Yes — this role is on-site at the client's NYC, NY location, five days per week. The client's culture and delivery cadence are calibrated around in-person collaboration for this position. Relocation support may be available for the right candidate; the recruiter will confirm during your calibration call.

Is this a permanent role?

Yes — this is a full time direct-hire position with the client. On offer acceptance, you onboard directly onto the client's payroll and benefits. ApTask's role is placement only; the recruiter stays in touch for the first 90 days as a check-in, but your day-to-day relationship is with the client's hiring manager.

What is the compensation range for this role?

The advertised range for this Principal GenAI Engineer role is $160,000–$200,000 per year. Where you land within the band depends on validated experience, the specific stack calibration match, and — for contract engagements — the bill-rate the client has locked in for this requisition. The recruiter will discuss the exact number during your calibration call.

How quickly does the interview process move?

If your profile is a fit for this role, you can expect the recruiter's first call within one business day. From there, interview cadence depends on the client's hiring-manager and panel availability. Total time from submission to signed offer varies by client — pre-verified profiles and calibrated submissions cut the noise, but the pace of interviews is driven by the client, not us.

What technical skills does the Principal GenAI Engineer role require?

The client is targeting depth in GenAI. Adjacent experience is welcome — we routinely place candidates whose exact stack match is 60-70% when the underlying pattern (distributed systems, regulated-data handling, or comparable) is strong. Bring the full stack breadth to your calibration call; the recruiter will map it onto the client's evaluation scorecard.

Principal GenAI Engineer

About the role

Required information for this posting

What this vertical looks like inside ApTask.

What happens after you apply.

1. Verified profile

2. Recruiter calibration call

3. Client interview

4. Offer + onboarding

Questions candidates ask about this role.

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What this vertical looks like inside ApTask.

What happens after you apply.

1. Verified profile

2. Recruiter calibration call

3. Client interview

4. Offer + onboarding

Questions candidates ask about this role.

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