AI Data Engineer Jobs at Tiger Analytics with Visa Sponsorship
AI Data Engineer jobs at Tiger Analytics involve building and scaling machine learning infrastructure and data pipelines for enterprise clients across industries. The company has an established sponsorship process covering multiple visa pathways, making it a realistic target if you're on OPT, H-1B visa, or pursuing permanent residence.
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Get Access To All JobsAbout Tiger Analytics
Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are a Great Place to Work-Certified™ company, recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG, and others.
Job Description
We are looking for a highly skilled Full Stack Gen AI Engineer with 7+ years of experience in software engineering, with a heavy focus on Python, AWS infrastructure, and Generative AI. The ideal candidate will be responsible for building high-performance API services and implementing complex RAG and Agentic AI architectures.
Key Requirements:
- Experience: Minimum of 7+ years of professional experience in software development and AI engineering
- API & Backend: Expert in building high-performance API / microservices using Python (FastAPI) deployed on AWS Fargate (ECS) (Most Critical)
- Generative AI Integration: Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers
- Infrastructure & DevOps: Experience with DevOps, CI/CD pipelines, and ML pipelines within the AWS ecosystem
- Agentic AI: Exposure to building Gen AI/Agentic AI applications, managing efficiency, latency, and backend infrastructure
- Technical Standards: Strong Python programming skills with a deep understanding of OpenAI API standards, JSON RESTful design, and LLM orchestration
Preferred Skills:
- Experience working with Bedrock Agent/Core services is a significant plus
Core Focus Areas & Expectations
Candidates will be expected to demonstrate deep technical proficiency in the following areas:
Why Join Us?
- Retrieval-Augmented Generation (RAG)
- Ability to design and implement end-to-end RAG pipelines, including retrievers, vector stores (e.g., Pinecone, Weaviate, or pgvector), and generators
- Expertise in latency optimization and relevance tuning to ensure production-grade performance
- Strategic approach to document chunking and embedding, balancing granularity with semantic coherence
- Agent Development
- Practical experience developing autonomous or semi-autonomous agents using frameworks such as LangChain, CrewAI, or Semantic Kernel
- Ability to manage orchestration, tool integration, and robust error handling for non-deterministic AI outputs
- Proficiency in managing memory and context (episodic vs. long-term) in multi-turn interactions and external API interfacing
- Evaluation and Optimization
- Familiarity with evaluation frameworks (e.g., RAGAS, TruLens) to assess performance, grounding accuracy, and hallucination detection
- Ability to iterate systems based on performance metrics and continuous improvement practices
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Every individual comes with a different set of skills and qualities, so even if you don't tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
About Tiger Analytics
Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are a Great Place to Work-Certified™ company, recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG, and others.
Job Description
We are looking for a highly skilled Full Stack Gen AI Engineer with 7+ years of experience in software engineering, with a heavy focus on Python, AWS infrastructure, and Generative AI. The ideal candidate will be responsible for building high-performance API services and implementing complex RAG and Agentic AI architectures.
Key Requirements:
- Experience: Minimum of 7+ years of professional experience in software development and AI engineering
- API & Backend: Expert in building high-performance API / microservices using Python (FastAPI) deployed on AWS Fargate (ECS) (Most Critical)
- Generative AI Integration: Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers
- Infrastructure & DevOps: Experience with DevOps, CI/CD pipelines, and ML pipelines within the AWS ecosystem
- Agentic AI: Exposure to building Gen AI/Agentic AI applications, managing efficiency, latency, and backend infrastructure
- Technical Standards: Strong Python programming skills with a deep understanding of OpenAI API standards, JSON RESTful design, and LLM orchestration
Preferred Skills:
- Experience working with Bedrock Agent/Core services is a significant plus
Core Focus Areas & Expectations
Candidates will be expected to demonstrate deep technical proficiency in the following areas:
Why Join Us?
- Retrieval-Augmented Generation (RAG)
- Ability to design and implement end-to-end RAG pipelines, including retrievers, vector stores (e.g., Pinecone, Weaviate, or pgvector), and generators
- Expertise in latency optimization and relevance tuning to ensure production-grade performance
- Strategic approach to document chunking and embedding, balancing granularity with semantic coherence
- Agent Development
- Practical experience developing autonomous or semi-autonomous agents using frameworks such as LangChain, CrewAI, or Semantic Kernel
- Ability to manage orchestration, tool integration, and robust error handling for non-deterministic AI outputs
- Proficiency in managing memory and context (episodic vs. long-term) in multi-turn interactions and external API interfacing
- Evaluation and Optimization
- Familiarity with evaluation frameworks (e.g., RAGAS, TruLens) to assess performance, grounding accuracy, and hallucination detection
- Ability to iterate systems based on performance metrics and continuous improvement practices
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Every individual comes with a different set of skills and qualities, so even if you don't tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
See all AI Data Engineer Jobs at Tiger Analytics
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Get Access To All JobsTips for Finding AI Data Engineer Jobs at Tiger Analytics
Align your portfolio with client-facing ML work
Tiger Analytics delivers analytics consulting to enterprise clients, so project examples showing end-to-end ML pipelines, cloud data architecture, or model deployment in a business context carry more weight than academic or personal projects.
Document your specialty occupation eligibility early
AI Data Engineer roles require USCIS to confirm the position qualifies as a specialty occupation. Gather transcripts, degree certificates, and employment letters that tie your computer science or data engineering credentials directly to the technical scope of the role.
Target Tiger Analytics roles before your OPT clock runs out
If you're on F-1 OPT, factor in that H-1B cap-subject petitions are filed in April for an October start. A role accepted in late summer may not leave enough buffer, so prioritize applications several months before your OPT expiration.
Confirm the LCA wage tier matches your experience level
Before accepting an offer, check DOL's Foreign Labor Certification Data Center to verify the prevailing wage level Tiger Analytics filed for comparable AI Data Engineer positions. Level I and Level II filings can significantly affect your negotiating position.
Use Migrate Mate to surface open AI Data Engineer roles at Tiger Analytics
Searching broadly misses roles that are actively sponsoring. Migrate Mate filters specifically for visa-sponsoring employers, so you can identify Tiger Analytics openings matched to your visa type without sifting through listings that won't consider international candidates.
Ask about PERM timing if long-term residency matters to you
Tiger Analytics has sponsored EB-2 and EB-3 Green Cards for engineering roles. During the offer stage, ask whether the company initiates PERM alongside your H-1B approval or waits, since early filing can significantly reduce your overall wait given per-country backlogs.
Frequently Asked Questions
Does Tiger Analytics sponsor H-1B visas for AI Data Engineers?
Yes, Tiger Analytics sponsors H-1B visas for AI Data Engineers. The company has an active sponsorship history covering cap-subject H-1B petitions and has also supported H-1B transfers for candidates already in valid status. If you're targeting an H-1B, confirm during the offer stage whether the role is structured for a change of status or consular processing, as this affects your timeline.
Which visa types does Tiger Analytics commonly use for AI Data Engineer roles?
Tiger Analytics sponsors H-1B, TN visa, F-1 OPT, F-1 CPT, and employment-based Green Cards including EB-2 and EB-3 for AI Data Engineer positions. F-1 candidates are commonly hired through OPT or CPT arrangements before transitioning to H-1B. TN visas apply specifically to Canadian and Mexican nationals in qualifying engineering or computer science roles.
What qualifications does Tiger Analytics expect for AI Data Engineer roles?
Tiger Analytics typically looks for a bachelor's or master's degree in computer science, data engineering, or a related field, combined with hands-on experience building production-grade ML pipelines and cloud data infrastructure. Proficiency in Python, SQL, and platforms such as AWS, Azure, or GCP is expected. Consulting-style communication skills matter here because engineers work directly with enterprise clients.
How do I apply for AI Data Engineer jobs at Tiger Analytics?
You can browse and apply for AI Data Engineer roles at Tiger Analytics through Migrate Mate, which filters listings specifically for visa-sponsoring employers so you can confirm sponsorship eligibility before applying. When you apply, tailor your resume to highlight data pipeline architecture, ML model deployment, and any enterprise or consulting-facing project experience, as these align with Tiger Analytics's delivery model.
How do I plan my application timeline if I need H-1B sponsorship at Tiger Analytics?
H-1B cap-subject petitions open in March for a lottery conducted in late March, with approved petitions taking effect October 1. If you're on F-1 OPT, you need employment to start before OPT expires, so accepting an offer by February or March gives Tiger Analytics enough runway to prepare the petition. USCIS premium processing is available and can reduce approval time to 15 business days.