STEM OPT Senior Data Science Engineer Jobs
Senior Data Science Engineer roles qualify for STEM OPT when your degree falls under an eligible CIP code in computer science, statistics, or a related STEM field. Your employer must be enrolled in E-Verify, and the 24-month extension gives you up to 36 months total to build experience, clear H-1B cap-gap, and transition to long-term sponsorship.
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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.
See all 577+ Senior Data Science Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Senior Data Science Engineer roles.
Get Access To All JobsTips for Finding STEM OPT Authorization as a Senior Data Science Engineer
Verify your CIP code before applying
Check that your degree's CIP code appears on the DHS STEM OPT designated degree program list. Computer science, statistics, and applied mathematics codes commonly support Senior Data Science Engineer roles, but data-adjacent business degrees may not qualify without a secondary STEM credential.
Confirm E-Verify enrollment before accepting offers
Ask recruiters directly whether the hiring entity, not just the parent company, is enrolled in E-Verify. Subsidiaries and staffing intermediaries sometimes operate under separate Employer Identification Numbers, so E-Verify enrollment at the wrong entity level can invalidate your STEM OPT extension.
File your I-983 training plan before day one
Your DSO must sign the I-983 before you start work. For Senior Data Science Engineer roles, map your training goals to specific project deliverables, model development cycles, and mentorship structures. A vague plan risks SEVP audit findings that can jeopardize your authorization.
Target employers with H-1B filing history
Use Migrate Mate to filter Senior Data Science Engineer roles by employers whose DOL Labor Condition Application history shows consistent STEM sponsorship. This removes companies that hire OPT students as short-term contractors but decline to support the H-1B transition you'll need before your 36 months run out.
Use OFLC Wage Search to benchmark your offer
Look up the prevailing wage for your SOC code and geographic area in OFLC Wage Search before negotiating. Your employer's LCA must certify at least the prevailing wage level, so an offer below that threshold is a compliance problem, not just a negotiation issue.
Start cap-gap planning at 24 months, not 36
If your employer files an H-1B petition before your STEM OPT expires and you're selected in the lottery, cap-gap rules extend your work authorization through September 30. Submit all supporting documents to USCIS promptly so there's no gap between your OPT end date and the H-1B start date.
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Find Senior Data Science Engineer JobsFrequently Asked Questions
Does a Senior Data Science Engineer role qualify for STEM OPT?
Yes, if your degree is listed on the DHS STEM OPT designated degree program list under an eligible CIP code, and the role requires that STEM knowledge in a direct, substantive way. Degrees in computer science, statistics, data science, and applied mathematics commonly support this role. Check your I-20 to confirm the CIP code your DSO recorded, because that code, not your job title, determines eligibility.
What E-Verify requirement applies to my STEM OPT employer?
Your employer must be actively enrolled in E-Verify at the specific worksite location where you'll work. Enrollment at a parent company or affiliated entity doesn't satisfy the requirement if you're employed by a subsidiary with a different EIN. Verify enrollment status directly with your recruiter or HR contact before signing an offer letter, since working for a non-enrolled employer voids your STEM OPT extension.
What goes into the I-983 training plan for a data science role?
The I-983 must describe the practical training goals, the skills you'll develop, and how those skills connect to your STEM degree. For a Senior Data Science Engineer position, this typically includes objectives around machine learning model development, data pipeline architecture, experimental design, and performance evaluation. Your employer's authorized representative and your DSO both sign the form, and it must be completed before your first day of work.
How does cap-gap work if I'm on STEM OPT and selected in the H-1B lottery?
If your employer files a timely H-1B petition on your behalf and USCIS selects it in the lottery, cap-gap automatically extends your work authorization from your OPT end date through September 30 of that year. Your H-1B then takes effect October 1. You can continue working during the cap-gap period as long as the petition remains pending or approved. Keep your I-20 and EAD documents current throughout this window.
Where can I find Senior Data Science Engineer jobs with verified STEM OPT sponsorship?
Migrate Mate lists Senior Data Science Engineer roles filtered for employers enrolled in E-Verify and with documented STEM sponsorship history based on DOL Labor Condition Application data. You can also cross-reference the O*NET profile for this occupation to identify the SOC code and confirm that your target roles align with your degree's CIP code before applying.
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