H-1B Visa AI Platform Engineer Jobs
AI Platform Engineer roles sit squarely within H-1B visa specialty occupation territory, requiring at least a bachelor's degree in computer science, machine learning, or a related field. Employers filing LCAs for this role typically classify it under SOC codes tied to software development or computer and information research, which affects your prevailing wage tier and petition strength.
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INTRODUCTION
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Job Description
What you will own
- One or more platform components end to end: model gateway (routing, failover, caching, per-line cost attribution), agent runtime and orchestration, evaluation harness, guardrail engine, tool and agent registry, or shared product services
- The training and adaptation loop: pipelines that turn production traces and evaluation verdicts into reinforcement learning and fine-tuning datasets, and the infrastructure to train, evaluate, and serve NewCo-tuned LLMs and SLMs behind the same gates as vendor models
- Reliability, latency, and cost of what you build; platform services carry baselines and you hold them
- The self-service surfaces product engineers use: your components ship with documentation, sane defaults, and no ticket queue
- Co-building with product teams: new shared services start embedded with a product line and graduate to platform services when proven
What you will need
- Strong production engineering: Python plus one systems language (Go or Rust welcome), Kubernetes, infrastructure-as-code, and one major cloud
- Hands-on experience with LLM infrastructure: a model gateway pattern (such as LiteLLM or in-house), model serving (such as vLLM or managed endpoints), and vector or retrieval systems
- Agent-systems experience: you have built with an agent orchestration framework (such as LangGraph or first-party agent SDKs) and understand tool calling and the Model Context Protocol (MCP)
- Evaluation engineering: you have built or operated eval harnesses (golden datasets, regression gates in CI, LLM-judge calibration) and can explain why they gate merges
- Post-training fluency: you have fine-tuned or post-trained a model, built the data pipeline behind one, or reproduced techniques from recent papers in production systems
- Daily, hands-on use of AI coding assistants as part of your own development workflow
We care about depth in four or five of these areas more than surface familiarity with all of them.
What sets you apart
- Guardrail-engine or AI-observability experience (NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust, or equivalent)
- Reinforcement learning infrastructure (reward modelling, RLHF or GRPO-class pipelines) or SLM distillation experience
- Multi-tenant SaaS infrastructure: tenancy isolation, metering, usage-based billing
- Financial services engineering (banks, insurers, or payment providers) is the ideal background; other regulated-industry or security engineering depth also counts
- Open-source contributions or a portfolio of deployed agents and eval suites (we would rather see this than a CV)
The reference stack
The reference technology stack for this role is our supported paved road: self-hosted LangSmith and LangGraph Platform as the agent runtime and evaluation plane, model providers behind a swappable gateway seam, PostgreSQL with pgvector plus ClickHouse and S3-compatible object storage as the data platform, Neo4j Enterprise as the semantic knowledge graph, an agent memory plane serving episodic and precedent memory over MCP, MCP-native connectors, OpenTelemetry and Grafana for observability, all on CNCF-conformant Kubernetes with Helm and Argo CD, deployable to any hyperscaler or on-prem. A tool-for-tool match is not expected: analogous experience counts fully. If you have built and operated systems of this shape on comparable components (a different orchestration framework, graph engine, evaluation platform, or serving stack), you have what we are looking for.
How we work
Engineers write specs, harnesses, evals, and guardrails; AI agents execute the implementation loops. Review, not typing, is where engineering judgment goes.
Three human gates govern everything we ship: spec approval, merge, and release. Regulated code paths (money movement, authentication, cryptography, secrets) are always human-owned.
COMPENSATION
The base compensation range for this role in the posted location is: 110000 to 139992
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
BENEFITS
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
See all 123+ H-1B Visa AI Platform Engineer Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Platform Engineer
Align your SOC code before negotiating
AI Platform Engineer roles get filed under different SOC codes depending on the employer, most often 15-1252 or 15-1299. The code drives your prevailing wage tier, so confirm which one your employer plans to use before the LCA is submitted.
Document your ML infrastructure work specifically
USCIS increasingly issues RFEs for platform engineering roles, questioning whether the position requires a specialty degree. Gather project artifacts, architecture diagrams, and performance benchmarks that tie your work directly to applied machine learning systems.
Search LCA filings to find proven sponsors
Use Migrate Mate to filter employers by verified H-1B LCA filing history for AI and platform engineering roles, so you're targeting companies that have already cleared the DOL certification process for positions like yours.
Check E-Verify enrollment before accepting an offer
If you're on STEM OPT and transitioning to H-1B, your current employer must be E-Verify enrolled. Confirm enrollment status with HR before your OPT end date, because a gap in authorization can't be retroactively fixed.
Use OFLC Wage Search to anchor your salary ask
Pull the prevailing wage for your target SOC code and work location using OFLC Wage Search before your offer conversation. Employers must pay at least the prevailing wage on the LCA, so knowing Level II versus Level III thresholds gives you a factual floor.
Time your cap-gap window against project timelines
If you're bridging OPT to H-1B under cap-gap, your authorization extends through September 30 but work authorization ends if USCIS denies the petition. Avoid accepting roles with critical delivery milestones that fall after that date without a contingency plan.
H-1B Visa AI Platform Engineer: Frequently Asked Questions
Does an AI Platform Engineer role qualify as a specialty occupation for H-1B purposes?
Yes, provided the position genuinely requires at least a bachelor's degree in a directly related field such as computer science, software engineering, or machine learning. USCIS scrutinizes platform engineering titles more than pure software roles, so the job description must clearly tie day-to-day responsibilities to a specific theoretical body of knowledge, not just general technical skill.
Which SOC code do employers typically use when filing H-1B petitions for AI Platform Engineers?
Most employers file under SOC 15-1252 (Software Developers) or 15-1299 (Computer Occupations, All Other), depending on how the role is structured. The SOC code determines the prevailing wage level your employer must certify on the LCA. You can verify which codes appear most often for this title by reviewing DOL disclosure data or searching employer LCA filings on Migrate Mate.
What makes H-1B RFEs more likely for AI Platform Engineer positions?
USCIS issues RFEs when the specialty occupation connection isn't obvious from the job description alone. Broad titles like 'platform engineer' or responsibilities that mix DevOps, infrastructure, and ML without anchoring them to a specific degree field raise adjudicator questions. Including architecture documentation, ML system design artifacts, and degree-specific role requirements in the initial petition significantly reduces RFE risk.
How do I find employers actively sponsoring H-1B visas for AI Platform Engineer roles?
Search Migrate Mate to browse AI Platform Engineer jobs filtered by employers with verified H-1B LCA filing history. This surfaces companies that have already completed DOL labor condition certification for similar roles, meaning they're familiar with the sponsorship process and less likely to withdraw an offer when they see the filing requirements.
Can my employer use premium processing for an AI Platform Engineer H-1B petition?
Yes. Premium processing is available for H-1B petitions and guarantees a USCIS decision within 15 business days. It's particularly useful for AI Platform Engineer roles where RFEs are more common, because a faster initial decision leaves more time to respond without disrupting your start date. Employers typically pay the premium processing fee, but confirm this during your offer negotiation.