STEM OPT AI Data Specialist Jobs
AI Data Specialist roles in machine learning, data labeling, and AI pipeline management qualify for STEM OPT because they sit under STEM-designated CIP codes in computer science and data science. Your employer must be enrolled in E-Verify, and your 24-month STEM OPT extension gives you up to 36 months total to build experience in this field.
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GenAI Engineer Applied AI Engineer LLM Agent Systems
Location
Onsite Charlotte NC
Addison TX
Jersey City NJ
Candidate must be willing to work onsite; remote is not an option.
Role Summary
We are seeking a highly skilled GenAI Engineer to design, build, and operationalize next-generation AI solutions leveraging Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG) architectures, and scalable cloud platforms. This role requires strong hands-on expertise across AI concepts, model integration, data pipelines, and MLOps/CICD with the ability to translate business problems into production-grade AI systems.
Key Responsibilities
GenAI LLM Engineering:
- Design, develop, and deploy LLM-powered applications using leading foundation models (OpenAI, Azure OpenAI, Anthropic, open-source LLMs).
- Build LLM-based AI agents capable of multistep reasoning, tool use, orchestration, and autonomous workflows.
- Implement and optimize agent frameworks (LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, etc.).
- Engineer robust prompting strategies, memory mechanisms, and tool-augmented reasoning.
RAG Knowledge Systems:
- Design and implement Retrieval-Augmented Generation (RAG) architectures.
- Build embedding pipelines using vector databases (FAISS, Pinecone, Weaviate, Azure AI Search, Chroma).
- Optimize document ingestion, chunking strategies, metadata management, and reranking.
- Ensure accuracy, relevance, and performance of AI-generated responses.
Machine Learning Model Integration:
- Apply practical ML concepts including classification, clustering, ranking, and similarity search where applicable.
- Integrate traditional ML models with LLM-based systems for hybrid AI solutions.
- Evaluate, fine-tune, and test models using appropriate performance metrics.
Data Engineering Pipelines:
- Develop and maintain data pipelines for structured and unstructured data using Python and SQL.
- Work with large datasets, APIs, and streaming/batch processing frameworks.
- Ensure data quality, lineage, observability, and governance within AI workflows.
MLOps CICD Productionization:
- Build CICD pipelines for AI and ML workloads including model versioning and automated testing.
- Deploy AI services in containerized environments (Docker, Kubernetes).
- Implement monitoring for model performance, drift, latency, and cost.
- Ensure security, access control, and compliance for AI systems.
Cloud Platform Engineering:
- Design and deploy AI solutions on cloud platforms such as AWS, Azure, or GCP.
- Leverage managed AIML services, serverless components, and scalable infrastructure.
- Optimize cost, performance, and reliability of AI workloads.
Collaboration Stakeholder Engagement:
- Partner with product, platform, and business teams to translate requirements into AI solutions.
- Document architectures, design decisions, and operational runbooks.
- Provide guidance on GenAI best practices, risks, and responsible AI usage.
Required Skills Experience
Core Technical Skills:
- Strong proficiency in Python and working knowledge of SQL.
- Solid foundation in AIML concepts with hands-on experience deploying models.
- Proven experience with LLMs, AI agents, and agent frameworks.
- Hands-on expertise with RAG architectures and vector databases.
- Experience implementing CICD pipelines for AI or ML systems.
- Strong understanding of data pipelines and distributed data processing.
- Experience working on at least one major cloud platform (AWS, Azure, or GCP).
Preferred Good to Have:
- Experience fine-tuning LLMs (LoRA, PEFT, RLHF concepts).
- Familiarity with evaluation frameworks for GenAI (hallucination testing, grounding, latency benchmarks).
- Exposure to governance, security, and compliance considerations for enterprise AI.
- Background in domains such as BFSI, healthcare, or regulated industries.
Education
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field or equivalent practical experience.
What Success Looks Like
- Scalable, reliable GenAI solutions deployed to production.
- Well-architected AI agents delivering measurable business value.
- High-quality, explainable, and maintainable AI systems.
- Strong collaboration across engineering, data, and business teams.
Skills
Mandatory Skills: GenAI - LLMOps, LLMOps
Benefits and Perks:
- Comprehensive Medical Plan Covering Medical, Dental, Vision
- Short Term and Long-Term Disability Coverage
- 401(k) Plan with Company match
- Life Insurance
- Vacation Time, Sick Leave, Paid Holidays
- Paid Paternity and Maternity Leave
The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay, and other forms of bonus or variable compensation.
Disclaimer: The compensation and benefits information provided herein is accurate as of the date of this posting.
LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.
Benefits
Compensation range: $93,000.00 to $142,000.00 per year
About LTM
LTM is an AI-centric global technology services company and the Business Creativity partner to the world’s largest and most disruptive enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI — enabling new ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM — a Larsen & Toubro company — owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it.
Please also note that neither LTM nor any of its authorized recruitment agencies/partners charge any candidate registration fee or any other fees from talent (candidates) towards appearing for an interview or securing employment/internship. Candidates shall be solely responsible for verifying the credentials of any agency/consultant that claims to be working with LTM for recruitment. Please note that anyone who relies on the representations made by fraudulent employment agencies does so at their own risk, and LTM disclaims any liability in case of loss or damage suffered as a consequence of the same.
Job Title
GenAI Engineer Applied AI Engineer LLM Agent Systems
Location
Onsite Charlotte NC
Addison TX
Jersey City NJ
Candidate must be willing to work onsite; remote is not an option.
Role Summary
We are seeking a highly skilled GenAI Engineer to design, build, and operationalize next-generation AI solutions leveraging Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG) architectures, and scalable cloud platforms. This role requires strong hands-on expertise across AI concepts, model integration, data pipelines, and MLOps/CICD with the ability to translate business problems into production-grade AI systems.
Key Responsibilities
GenAI LLM Engineering:
- Design, develop, and deploy LLM-powered applications using leading foundation models (OpenAI, Azure OpenAI, Anthropic, open-source LLMs).
- Build LLM-based AI agents capable of multistep reasoning, tool use, orchestration, and autonomous workflows.
- Implement and optimize agent frameworks (LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, etc.).
- Engineer robust prompting strategies, memory mechanisms, and tool-augmented reasoning.
RAG Knowledge Systems:
- Design and implement Retrieval-Augmented Generation (RAG) architectures.
- Build embedding pipelines using vector databases (FAISS, Pinecone, Weaviate, Azure AI Search, Chroma).
- Optimize document ingestion, chunking strategies, metadata management, and reranking.
- Ensure accuracy, relevance, and performance of AI-generated responses.
Machine Learning Model Integration:
- Apply practical ML concepts including classification, clustering, ranking, and similarity search where applicable.
- Integrate traditional ML models with LLM-based systems for hybrid AI solutions.
- Evaluate, fine-tune, and test models using appropriate performance metrics.
Data Engineering Pipelines:
- Develop and maintain data pipelines for structured and unstructured data using Python and SQL.
- Work with large datasets, APIs, and streaming/batch processing frameworks.
- Ensure data quality, lineage, observability, and governance within AI workflows.
MLOps CICD Productionization:
- Build CICD pipelines for AI and ML workloads including model versioning and automated testing.
- Deploy AI services in containerized environments (Docker, Kubernetes).
- Implement monitoring for model performance, drift, latency, and cost.
- Ensure security, access control, and compliance for AI systems.
Cloud Platform Engineering:
- Design and deploy AI solutions on cloud platforms such as AWS, Azure, or GCP.
- Leverage managed AIML services, serverless components, and scalable infrastructure.
- Optimize cost, performance, and reliability of AI workloads.
Collaboration Stakeholder Engagement:
- Partner with product, platform, and business teams to translate requirements into AI solutions.
- Document architectures, design decisions, and operational runbooks.
- Provide guidance on GenAI best practices, risks, and responsible AI usage.
Required Skills Experience
Core Technical Skills:
- Strong proficiency in Python and working knowledge of SQL.
- Solid foundation in AIML concepts with hands-on experience deploying models.
- Proven experience with LLMs, AI agents, and agent frameworks.
- Hands-on expertise with RAG architectures and vector databases.
- Experience implementing CICD pipelines for AI or ML systems.
- Strong understanding of data pipelines and distributed data processing.
- Experience working on at least one major cloud platform (AWS, Azure, or GCP).
Preferred Good to Have:
- Experience fine-tuning LLMs (LoRA, PEFT, RLHF concepts).
- Familiarity with evaluation frameworks for GenAI (hallucination testing, grounding, latency benchmarks).
- Exposure to governance, security, and compliance considerations for enterprise AI.
- Background in domains such as BFSI, healthcare, or regulated industries.
Education
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field or equivalent practical experience.
What Success Looks Like
- Scalable, reliable GenAI solutions deployed to production.
- Well-architected AI agents delivering measurable business value.
- High-quality, explainable, and maintainable AI systems.
- Strong collaboration across engineering, data, and business teams.
Skills
Mandatory Skills: GenAI - LLMOps, LLMOps
Benefits and Perks:
- Comprehensive Medical Plan Covering Medical, Dental, Vision
- Short Term and Long-Term Disability Coverage
- 401(k) Plan with Company match
- Life Insurance
- Vacation Time, Sick Leave, Paid Holidays
- Paid Paternity and Maternity Leave
The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay, and other forms of bonus or variable compensation.
Disclaimer: The compensation and benefits information provided herein is accurate as of the date of this posting.
LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, color, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.
Benefits
Compensation range: $93,000.00 to $142,000.00 per year
About LTM
LTM is an AI-centric global technology services company and the Business Creativity partner to the world’s largest and most disruptive enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI — enabling new ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM — a Larsen & Toubro company — owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it.
Please also note that neither LTM nor any of its authorized recruitment agencies/partners charge any candidate registration fee or any other fees from talent (candidates) towards appearing for an interview or securing employment/internship. Candidates shall be solely responsible for verifying the credentials of any agency/consultant that claims to be working with LTM for recruitment. Please note that anyone who relies on the representations made by fraudulent employment agencies does so at their own risk, and LTM disclaims any liability in case of loss or damage suffered as a consequence of the same.
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Get Access To All JobsTips for Finding STEM OPT Authorization as an AI Data Specialist
Verify your CIP code before applying
Check that your degree's CIP code is on the STEM Designated Degree Program List maintained by ICE. Computer science (11.07), data science (11.04), and statistics (27.05) all qualify, but interdisciplinary AI programs can vary by institution.
Screen job postings for E-Verify enrollment
Before sending any application, confirm the employer is enrolled in E-Verify through the E-Verify employer search. Sponsors who aren't enrolled cannot legally hire STEM OPT students, and postings rarely flag this gap upfront.
Align your I-983 training plan to AI Data Specialist duties
Your I-983 must tie your training objectives to specific role tasks, such as data annotation, model evaluation, or pipeline QA. Vague plans get flagged by DSOs, so map each objective to a concrete deliverable your manager can describe.
Target employers with active LCA filings in AI roles
Use Migrate Mate to filter employers by Labor Condition Application filings under AI and data science job categories, so you're targeting companies that have already filed the DOL paperwork for roles matching your background.
Negotiate your start date around OPT cap-gap timing
If your initial 12-month OPT expires while an H-1B petition is pending, cap-gap rules let you keep working. Confirm your offer letter start date leaves enough lead time for your DSO to authorize the STEM OPT extension before your current EAD runs out.
Pull prevailing wage data before every offer evaluation
Run the AI Data Specialist SOC code through the OFLC Wage Search to see the Level I through Level IV prevailing wage for your metro area. Your offer must meet the prevailing wage for any future LCA your employer files.
AI Data Specialist jobs are hiring across the US. Find yours.
Find AI Data Specialist JobsFrequently Asked Questions
Does my degree qualify me for the STEM OPT extension as an AI Data Specialist?
Your degree qualifies if it carries a STEM-designated CIP code, such as computer science, data science, statistics, or a related engineering field. The role itself doesn't determine eligibility; your degree program does. Check the ICE STEM Designated Degree Program List against your transcript's CIP code, and confirm with your DSO before applying for positions.
What E-Verify requirement applies to my STEM OPT employer?
Every employer that hires a STEM OPT student must be enrolled in E-Verify at the specific worksite where you'll work. If your company uses a staffing agency or a third-party client site, the end client must also be enrolled. USCIS requires your DSO to confirm E-Verify enrollment before authorizing your STEM OPT extension, so verify this before accepting an offer.
What should the I-983 training plan include for an AI Data Specialist role?
Your I-983 must describe how the position provides practical training in your STEM field. For AI Data Specialist roles, that means listing specific learning objectives tied to tasks like data labeling methodologies, model performance evaluation, dataset quality assurance, or annotation pipeline management. Your supervisor must sign off on the plan, and your DSO reviews it for academic relevance before approving the extension.
How do I find AI Data Specialist jobs at companies enrolled in E-Verify?
Use Migrate Mate to search AI Data Specialist roles filtered for STEM OPT eligibility. The platform surfaces employers with verified E-Verify enrollment and active Labor Condition Application filings, so you're not spending time applying to companies that can't legally hire STEM OPT students. Standard job boards don't filter for E-Verify status, which makes this the most direct approach.
What happens to my STEM OPT work authorization if I receive an H-1B and my EAD expires before October 1?
Cap-gap protection automatically extends your work authorization if your H-1B petition is filed before your OPT EAD expires and your petition is selected in the lottery. You can keep working under cap-gap until October 1, when the new H-1B fiscal year begins. USCIS confirms cap-gap eligibility on your I-20, which your DSO updates once your employer files the H-1B petition.
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