Software Development Engineer II, Generative AI

Jersey City, NJ, US Mid Level AI Product Manager

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Skills & Technologies

EmbeddingsPrompt EngineeringPythonRag

About This Role

AI job market dashboard showing open roles by category

This is a hands-on engineering role for someone who wants to build real GenAI systems — not prototypes. You'll work across the full lifecycle, from experimentation and prompt/RAG design through production deployment, observability, and iteration, partnering closely with senior engineers, product owners, and technical leadership.

  • Build features and components for production-grade GenAI products, with a focus on quality, reliability, and performance.
  • Implement and iterate on LLM-based solutions, including retrieval-augmented generation (RAG), prompt engineering, context Engineering, Loop Engineering and agentic workflows.
  • Write clean, well-tested, maintainable Python code and contribute to the broader codebase and infrastructure.
  • Help build evaluation and monitoring pipelines to measure output quality, groundedness, and reliability of GenAI features.
  • Work with foundation models and GenAI frameworks/tooling, evaluating tradeoffs between approaches under guidance from senior engineers.
  • Collaborate with Product Owners and cross-functional stakeholders to translate requirements into working technical solutions.
  • Participate in code reviews, design discussions, and engineering best practices across the GenAI development lifecycle.
  • Debug and resolve technical issues across the stack, escalating and collaborating with senior team members on complex problems.
  • (SDE II) Take ownership of medium-complexity features end-to-end, mentor SDE I engineers, and contribute to architecture and design decisions for GenAI components.
  • 3+ years of industry experience in software engineering, data science, or machine learning.
  • 1+ years of hands-on experience building GenAI/LLM-based features or applications, ideally in a production setting.
  • Strong Python skills and experience with modern AI/ML and GenAI frameworks and tooling.
  • Working understanding of LLMs, embeddings, RAG, prompt engineering, context Engineering, and GenAI architecture patterns.
  • Experience with cloud-native architectures and deploying scalable applications to production.
  • Understanding of GenAI evaluation, testing, monitoring, and responsible AI practices.
  • Ability to work with moderate autonomy, break down ambiguous problems, and communicate technical tradeoffs clearly.
  • Genuine curiosity and enthusiasm for learning new technologies, tools, and techniques in a fast-moving field.

Bachelor's degree in Computer Science, Software Engineering, Machine Learning, Data Science, or a related technical field. *

Additional Qualifications

  • knowledge on fine-tuning or adapting LLMs (e.g., SFT, LoRA/PEFT, instruction tuning), including preparing training datasets or evaluating fine-tuned models against baselines is a plus.
  • Experience with agentic AI patterns or multi-step LLM workflows is a plus.

#LI-MB1

#LI-Hybrid

For over 50 years, Verisk has been the leading data analytics and technology partner to the global insurance industry by delivering value to our clients through expertise and scale. We empower communities and businesses to make better decisions on risk, faster.

At Verisk, you'll have the chance to use your voice and build a rewarding career that's as unique as you are, with work flexibility and the support, coaching, and training you need to succeed.

For the eighth consecutive year, Verisk is proudly recognized as a Great Place to Work® for outstanding workplace culture in the US, the fourth consecutive year in the UK, Spain, and India, and the second consecutive year in Poland. In addition, we’ve been recognized by The Wall Street Journal as one of the Best-Managed Companies and by Forbes as a World’s Best Employer, testaments to the value we place on workplace culture.

We’re 7,000 people strong. We relentlessly and ethically pursue innovation. And we are looking for people like you to help us translate big data into big ideas. Join us and create an exceptional experience for yourself and a better tomorrow for future generations.

Verisk Businesses

Underwriting Solutions — provides underwriting and rating solutions for auto and property, general liability, and excess and surplus to assess and price risk with speed and precision

Claims Solutions — supports end-to-end claims handling with analytic and automation tools that streamline workflow, improve claims management, and support better customer experiences

Property and Restoration Solutions — offers property estimation software and tools for professionals in estimating all phases of building and repair to make day-to-day workflows the most efficient

Specialty Business Solutions — provides an integrated suite of software for full end-to-end management of insurance and reinsurance business, helping companies manage their businesses through efficiency, flexibility, and data governance

Catastrophe and Risk Solutions — provides risk modeling solutions to help individuals, businesses, and society become more resilient to catastrophic events.

Marketing Solutions — delivers data and insights to improve the reach, timing,relevance, and compliance of every consumer engagement

Life Insurance Solutions – offers end-to-end, data insight-driven core capabilities for carriers, distribution, and direct customers across the entire policy lifecycle of life and annuities for both individual and group.

Verisk Maplecroft — provides intelligence on sustainability, resilience, and ESG, helping people, business, and societies become stronger

Verisk Analytics is an equal opportunity employer.

Verisk invests in a benefits package for all employees that includes the following: Health Insurance, a Retirement Plan, Disability benefits, and a Paid Time Off program. We offer a competitive total rewards package that includes base salary determined based on role, experience, skill set, and location.

All members of the Verisk Analytics family of companies are equal opportunity employers. We consider all qualified applicants for employment without regard to race, religion, color, national origin, citizenship, sex, gender identity and/or expression, sexual orientation, veteran's status, age or disability. Verisk’s minimum hiring age is 18 except in countries with a higher age limit subject to applicable law.

https://www.verisk.com/company/careers/

Unsolicited resumes sent to Verisk, including unsolicited resumes sent to a Verisk business mailing address, fax machine or email address, or directly to Verisk employees, will be considered Verisk property. Verisk will NOT pay a fee for any placement resulting from the receipt of an unsolicited resume.

Verisk Employee Privacy Notice

Role Details

Title Software Development Engineer II, Generative AI
Location Jersey City, NJ, US
Experience Mid Level
Salary Not disclosed
Remote No

About This Role

AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.

Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.

Across the 11,520 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Ignite Insurance Systems, this role fits into their broader AI and engineering organization.

AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.

What the Work Looks Like

A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.

AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.

Skills Required

Embeddings (3% of roles) Prompt Engineering (4% of roles) Python (20% of roles) Rag (8% of roles)

Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.

The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.

Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.

Compensation Benchmarks

AI Product Manager roles pay a median of $220,200 based on 993 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.

Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.

Ignite Insurance Systems AI Hiring

Ignite Insurance Systems has 3 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, AI Architect. Based in Jersey City, NJ, US.

Location Context

Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).

Career Path

Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.

From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.

The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.

What to Expect in Interviews

AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.

When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.

AI Hiring Overview

The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.

The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).

AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.

The AI Job Market Today

The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 993 roles with disclosed compensation, the median salary for AI Product Manager positions is $220,200. Actual compensation varies by seniority, location, and company stage.
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
About 6% of the 11,520 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Ignite Insurance Systems is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Product Manager positions include Director of AI Product, VP Product, Head of AI. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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