Manager, Generative AI
Fa Ewmy Saasfaprod1 Open · verified Oct 22, 2026 At a glance
Manager-level AI Engineering role at Fa Ewmy Saasfaprod1. Jersey City · full-time · no salary stated · we estimate $132,450–$205,151 across the United States.
Fa Ewmy Saasfaprod1 has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Guide and coach a distributed engineering team, combining technical direction with performance management
- Take GenAI products from architecture and experimentation through production, balancing security, reliability, quality and cost
- Choose approaches for LLMs, retrieval, fine-tuning, prompts and agent-based systems
- Set up ways to evaluate, test and monitor GenAI products, including checks for groundedness and reliability
- Turn business needs into technical plans, make model and build-versus-buy choices, and communicate risks and tradeoffs
What you bring
- At least seven years in software engineering, data science or machine learning, including technical leadership
- At least two years building and delivering Generative AI or LLM solutions hands-on
- A bachelor's degree in computer science, software engineering or another listed technical field
- Strong Python skills and practical knowledge of LLMs, RAG, embeddings, prompt design and cloud-based production systems
Who this fits
This role suits a hands-on technical leader who can guide engineers while shaping and delivering production AI systems. The team is globally distributed, and the position is based in Jersey City with a hybrid arrangement.
From the employer
Verisk ISO Corelines is seeking a highly technical Manager, Generative AI to lead a globally distributed team of engineers responsible for developing and delivering production-grade Generative AI products.
This is a hands-on technical leadership role combining strong software engineering and AI/ML expertise with people leadership. You will help define the technical direction for GenAI capabilities, translate business opportunities into scalable solutions, and lead products from concept and experimentation through production deployment.
What you’ll do
- Lead and develop globally distributed engineering teams through hands-on technical leadership, performance management, mentoring, and coaching.
- Lead the architecture, design, development, and delivery of production-grade GenAI products, ensuring quality, security, scalability, reliability, performance, and cost effectiveness.
- Guide technical decisions involving LLMs, RAG, model fine-tuning/customization, prompt engineering, and agentic AI patterns.
- Establish effective approaches for GenAI evaluation, testing, observability, and production monitoring, including measurement of quality, groundedness, and reliability.
- Evaluate foundation models, AI platforms, and emerging technologies and make appropriate architecture, model-selection, and build-vs-buy decisions.
- Partner with Product Owners and business stakeholders to translate business needs into technical requirements, architectures, and delivery plans.
- Drive engineering best practices across the GenAI development lifecycle and resolve complex technical and delivery challenges.
- Communicate technical decisions, tradeoffs, project status, risks, and priorities effectively with engineering teams and senior stakeholders.
What you bring
- 7+ years of industry experience in software engineering, data science, or machine learning, including technical leadership experience.
- 2+ years of hands-on experience building and delivering Generative AI/LLM solutions, preferably production applications.
- Proven experience architecting and operating large-scale production software, AI/ML systems, and/or data platforms.
- Strong understanding of LLMs, embeddings, RAG, prompt engineering, context management, and modern GenAI architectures.
- Strong Python skills and experience with modern AI/ML and GenAI frameworks and tooling.
- Experience with cloud-native architectures and production deployment of scalable applications.
- Strong understanding of GenAI evaluation, testing, monitoring, security, and responsible AI practices.
- Ability to translate business requirements into technical solutions and communicate complex technical decisions to both engineering and executive audiences.
- Bachelor’s degree in Computer Science, Software Engineering, Machine Learning, Data Science, or a related technical field.
Preferred Qualifications
- Hands-on experience fine-tuning or adapting LLMs, including techniques such as SFT, LoRA/PEFT, instruction tuning, or related approaches, with experience preparing training datasets and evaluating fine-tuned models against appropriate baselines.