Transportation H-1B1 Singapore Sponsorship Jobs in New York
H-1B1 Singapore visa sponsorship jobs in New York's transportation sector span freight logistics, supply chain management, and infrastructure planning across major hubs like New York City, Albany, and Buffalo. Employers including freight carriers, port operators, and transit authorities have filed H-1B1 Singapore LCAs for specialty occupation roles requiring at least a bachelor's degree in a directly related field.
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Get Access To All JobsAbout the Role
The AI Knowledge Architect (customer support) role sits within the Global Digital Experience (GDX) team and is responsible for building and maintaining the knowledge portion of the brain of our customer-facing AI agents. You will develop the knowledge needed by LLMs to craft empathetic responses, design conversational logic, and provide business context that allow our AI agents to respond against complex customer problems autonomously. You will be the connector between expressed customer requests, support policies and customer data and convert these into intuitive, empathetic and brand-aligned AI responses.
Your role requires a combination of skills - precision of a Technical Writer, empathy of a UX Designer, and the logic of a Prompt Engineer. Your role starts with writing articles but extends to structuring knowledge so an AI agent can reason, retrieve, and act upon it accurately.
This role sits at the intersection of Community Operations (CommOps) and Customer Obsession (CO) Product. You will work closely with CommOps frontline teams to deeply understand their customer requirements and collaborate with engineering and product teams to build knowledge that optimizes segmented customer experience.
What the Candidate Will Do
-
AI Knowledge authoring: Author and structure prompt-aware content for AI agents to ensure the AI provides accurate, empathetic responses without hallucinations. Decide where the AI does not need any additional content, where it needs some context, where it can pull data from upstream systems for context and where it needs a lot of details, and tailor knowledge accordingly. Incorporate tribal knowledge from various parts of Uber into the knowledge base to ensure the AI agents are able to respond to customer queries effectively.
-
AI Information architecture: Ensure the content provided to the AI agents are relevant, accurate, updated, non-conflicting and succinct. Identify gaps in content leading to AI agents not being able to help customers or providing wrong responses and fix those quickly. Ensure easy knowledge access for AI agents (e.g., clean up metadata where needed, improve vector match probabilities, decide how to chunk knowledge so that retrieval is highly accurate and efficient from a latency and cost perspective).
-
AI Performance Tuning and standards improvement: Analyze failed AI conversations to identify knowledge gaps, then update documentation or metadata to improve future performance. Use your knowledge of the Tech stack to ensure retrieval accuracy is high and AI responses are crafted according to segmentation requirements and decision logic. Provide feedback to the Global Content team to improve content standards in case they are hindering the delivery of good responses.
-
Product Thinking: Provide feedback to product and Engineering teams to improve prompts to effectively leverage AI knowledge and on platform enhancements needed for authoring effective AI knowledge. Operate in an agile fashion to adapt knowledge to Technology and product advancements in a rapidly changing AI ecosystem.
-
Experiment with Knowledge options: Lead the product and use case evolution to better response patterns by experimenting with options to decide what amount of deterministic knowledge inputs is necessary and where to depend on LLM reasoning.
-
Cross-functional Partnership: Engage deeply with CommOps teams to identify customer experience needs and usability requirements for AI agents and address them through knowledge improvements. Engage with the Global Content team to ensure content standards, tone of voice and strategy is adhered to. Engage with Legal teams where relevant to get relevant approvals for the knowledge created.
Basic Qualifications
- 8+ years of experience in Technical Writing, Information Architecture, Conversation Design, or Product Operations
- 1+ year of demonstrated hands-on work with AI Knowledge
Preferred Qualifications
- Experience of working with leading LLMs (e.g., GPT-4, Claude, Gemini) and Gen AI concepts like RAG, Agentic AI, chain-of-thought prompting, decision flows, AI reasoning, etc.
- Excellent collaboration skills with both technical (e.g., product managers, engineers, data scientists, and UX teams) and non-technical stakeholders
- Systems thinking, especially ability to identify downstream implications of knowledge gaps and judgment around edge cases, ambiguity, and exception handling
- Strong business acumen and customer understanding; exposure to cognitive sciences is a plus
- Analytical mindset with attention to precision and clarity; ability to read latency and accuracy logs to see where the AI "got lost" in the knowledge base
- Understanding of semantic precision in the AI context
- Ability to thrive in a fast-paced, ambiguous environment
- Experience in Operations or program management is a plus
- Experience of working on human-computer interactions is a plus
- Exceptional verbal communication skills
- Familiarity with SQL, Python, JSON, etc is a plus
Compensation
- For Chicago, IL-based roles: The base salary range for this role is USD$146,000 per year - USD$162,000 per year.
- For New York, NY-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
- For San Francisco, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
- For Seattle, WA-based roles: The base salary range for this role is USD$146,000 per year - USD$162,000 per year.
- For Sunnyvale, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
About the Role
The AI Knowledge Architect (customer support) role sits within the Global Digital Experience (GDX) team and is responsible for building and maintaining the knowledge portion of the brain of our customer-facing AI agents. You will develop the knowledge needed by LLMs to craft empathetic responses, design conversational logic, and provide business context that allow our AI agents to respond against complex customer problems autonomously. You will be the connector between expressed customer requests, support policies and customer data and convert these into intuitive, empathetic and brand-aligned AI responses.
Your role requires a combination of skills - precision of a Technical Writer, empathy of a UX Designer, and the logic of a Prompt Engineer. Your role starts with writing articles but extends to structuring knowledge so an AI agent can reason, retrieve, and act upon it accurately.
This role sits at the intersection of Community Operations (CommOps) and Customer Obsession (CO) Product. You will work closely with CommOps frontline teams to deeply understand their customer requirements and collaborate with engineering and product teams to build knowledge that optimizes segmented customer experience.
What the Candidate Will Do
-
AI Knowledge authoring: Author and structure prompt-aware content for AI agents to ensure the AI provides accurate, empathetic responses without hallucinations. Decide where the AI does not need any additional content, where it needs some context, where it can pull data from upstream systems for context and where it needs a lot of details, and tailor knowledge accordingly. Incorporate tribal knowledge from various parts of Uber into the knowledge base to ensure the AI agents are able to respond to customer queries effectively.
-
AI Information architecture: Ensure the content provided to the AI agents are relevant, accurate, updated, non-conflicting and succinct. Identify gaps in content leading to AI agents not being able to help customers or providing wrong responses and fix those quickly. Ensure easy knowledge access for AI agents (e.g., clean up metadata where needed, improve vector match probabilities, decide how to chunk knowledge so that retrieval is highly accurate and efficient from a latency and cost perspective).
-
AI Performance Tuning and standards improvement: Analyze failed AI conversations to identify knowledge gaps, then update documentation or metadata to improve future performance. Use your knowledge of the Tech stack to ensure retrieval accuracy is high and AI responses are crafted according to segmentation requirements and decision logic. Provide feedback to the Global Content team to improve content standards in case they are hindering the delivery of good responses.
-
Product Thinking: Provide feedback to product and Engineering teams to improve prompts to effectively leverage AI knowledge and on platform enhancements needed for authoring effective AI knowledge. Operate in an agile fashion to adapt knowledge to Technology and product advancements in a rapidly changing AI ecosystem.
-
Experiment with Knowledge options: Lead the product and use case evolution to better response patterns by experimenting with options to decide what amount of deterministic knowledge inputs is necessary and where to depend on LLM reasoning.
-
Cross-functional Partnership: Engage deeply with CommOps teams to identify customer experience needs and usability requirements for AI agents and address them through knowledge improvements. Engage with the Global Content team to ensure content standards, tone of voice and strategy is adhered to. Engage with Legal teams where relevant to get relevant approvals for the knowledge created.
Basic Qualifications
- 8+ years of experience in Technical Writing, Information Architecture, Conversation Design, or Product Operations
- 1+ year of demonstrated hands-on work with AI Knowledge
Preferred Qualifications
- Experience of working with leading LLMs (e.g., GPT-4, Claude, Gemini) and Gen AI concepts like RAG, Agentic AI, chain-of-thought prompting, decision flows, AI reasoning, etc.
- Excellent collaboration skills with both technical (e.g., product managers, engineers, data scientists, and UX teams) and non-technical stakeholders
- Systems thinking, especially ability to identify downstream implications of knowledge gaps and judgment around edge cases, ambiguity, and exception handling
- Strong business acumen and customer understanding; exposure to cognitive sciences is a plus
- Analytical mindset with attention to precision and clarity; ability to read latency and accuracy logs to see where the AI "got lost" in the knowledge base
- Understanding of semantic precision in the AI context
- Ability to thrive in a fast-paced, ambiguous environment
- Experience in Operations or program management is a plus
- Experience of working on human-computer interactions is a plus
- Exceptional verbal communication skills
- Familiarity with SQL, Python, JSON, etc is a plus
Compensation
- For Chicago, IL-based roles: The base salary range for this role is USD$146,000 per year - USD$162,000 per year.
- For New York, NY-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
- For San Francisco, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
- For Seattle, WA-based roles: The base salary range for this role is USD$146,000 per year - USD$162,000 per year.
- For Sunnyvale, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Transportation Job Roles in New York
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Search Transportation Jobs in New YorkTransportation Jobs in New York: Frequently Asked Questions
Which transportation companies sponsor H-1B1 Singapore visas in New York?
New York transportation employers that have filed Labor Condition Applications for H-1B1 Singapore workers include freight and logistics companies, intermodal operators at the Port of New York and New Jersey, airline ground operations firms, and supply chain consulting groups. Transit authorities and infrastructure planning firms in the New York metropolitan area have also filed LCAs for specialty occupation roles. Sponsorship history varies by company and fiscal year, so reviewing DOL OFLC disclosure data gives the clearest picture of active filers.
Which cities in New York have the most transportation H-1B1 Singapore sponsorship jobs?
New York City accounts for the largest share of H-1B1 visa Singapore transportation sponsorship activity in the state, driven by its concentration of logistics firms, freight forwarders, and aviation operations at JFK and LaGuardia. Buffalo and Albany see activity from supply chain and infrastructure roles tied to regional freight corridors and state transportation agencies. Long Island hosts warehousing and distribution employers that have filed LCAs for operations and planning roles.
What types of transportation roles typically qualify for H-1B1 Singapore sponsorship?
Roles that qualify must meet the specialty occupation standard, requiring at least a bachelor's degree in a directly related field. In transportation, qualifying positions commonly include supply chain analysts, logistics engineers, transportation planners, operations research analysts, and freight network optimization specialists. Roles in port operations management, aviation operations analysis, and infrastructure project coordination have also appeared in LCA filings. General driving, warehousing, or trade roles that do not require a specific degree typically do not qualify.
How do I find transportation H-1B1 Singapore sponsorship jobs in New York?
Migrate Mate filters job listings specifically by visa type, letting you search for transportation roles in New York where employers have H-1B1 Singapore LCA filing history. This removes the guesswork of identifying which companies actually sponsor the visa. You can narrow results by city, role type, and industry segment within transportation and logistics. Reviewing DOL OFLC disclosure data alongside your Migrate Mate search helps you verify an employer's sponsorship track record before applying.
Are there state-specific considerations for H-1B1 Singapore sponsorship in New York's transportation sector?
New York employers must comply with state labor law posting requirements in addition to federal DOL LCA obligations, including posting notices at the actual worksite for the duration of the LCA validity period. Transportation roles involving multiple worksites, such as positions that rotate between freight terminals or construction sites across the state, require employers to file amended LCAs or blanket LCA coverage for each location. New York City's prevailing wage determinations can also exceed national OFLC wage levels, which affects the wage employers must certify on the LCA.
What is the prevailing wage for H-1B1 Singapore transportation jobs in New York?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.