OPT AI Research Engineer Jobs
AI Research Engineer roles sit at the intersection of machine learning research and production systems, making them one of the most competitive OPT job categories. Most positions require a master's or PhD and fall squarely within STEM OPT, giving you up to 36 months of work authorization to establish yourself in U.S. research teams.
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BeaconFire is based in Central NJ, specializing in Software Development, Web Development, and Business Intelligence; looking for a strong agentic AI developer who can build and productionize Vertex AI–based RAG systems (Vertex AI Search / Vertex AI RAG patterns), design reliable tool-using agents, and work comfortably with vector databases and graph databases.
About the Role
You’ll own end-to-end delivery: ingestion, retrieval, agent orchestration, evaluation, and deployment.
Responsibilities
- Collaborate with the team to design and develop high quality Web applications using Python, Flask, Django, and related technologies.
- Write clean and efficient code, and ensure code maintainability and reusability.
- Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding).
- Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks.
- Perform code reviews to ensure code quality and consistency.
- Conduct testing to ensure application quality and reliability.
- Create and maintain technical documentation for web applications.
- Participate in project planning, estimation, and prioritization.
- Stay up to date with the latest technologies for Python development.
- Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively.
- Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices.
Qualifications
- Experience in software development in Python3.
- Decent understanding of the software development/testing life cycle.
- Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc).
- Experience with version control tools, such as Git.
- Experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design).
- Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns.
- Solid knowledge of vector search concepts and at least one vector DB in production.
- Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset.
Preferred Skills
- Master’s Degree in Computer Science, Software Engineering, or related field.
- 1+ year professional experience in Python web application development with either Flask or Django.
- Experience in RESTful API development in Python.
- Understanding of Python web application frameworks such as Flask or Django.
- Experience with Cloud services, such as AWS.
- Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, CloudRun/GKE, storage).
- Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion).
- Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval.
- Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management.
- Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling).
Pay range and compensation package
BeaconFire is an E-verified company and provides equal employment opportunities (visa sponsorship provided).
Equal Opportunity Statement
BeaconFire is committed to diversity and inclusivity.
About the Company
BeaconFire is based in Central NJ, specializing in Software Development, Web Development, and Business Intelligence; looking for a strong agentic AI developer who can build and productionize Vertex AI–based RAG systems (Vertex AI Search / Vertex AI RAG patterns), design reliable tool-using agents, and work comfortably with vector databases and graph databases.
About the Role
You’ll own end-to-end delivery: ingestion, retrieval, agent orchestration, evaluation, and deployment.
Responsibilities
- Collaborate with the team to design and develop high quality Web applications using Python, Flask, Django, and related technologies.
- Write clean and efficient code, and ensure code maintainability and reusability.
- Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding).
- Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks.
- Perform code reviews to ensure code quality and consistency.
- Conduct testing to ensure application quality and reliability.
- Create and maintain technical documentation for web applications.
- Participate in project planning, estimation, and prioritization.
- Stay up to date with the latest technologies for Python development.
- Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively.
- Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices.
Qualifications
- Experience in software development in Python3.
- Decent understanding of the software development/testing life cycle.
- Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc).
- Experience with version control tools, such as Git.
- Experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design).
- Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns.
- Solid knowledge of vector search concepts and at least one vector DB in production.
- Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset.
Preferred Skills
- Master’s Degree in Computer Science, Software Engineering, or related field.
- 1+ year professional experience in Python web application development with either Flask or Django.
- Experience in RESTful API development in Python.
- Understanding of Python web application frameworks such as Flask or Django.
- Experience with Cloud services, such as AWS.
- Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, CloudRun/GKE, storage).
- Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion).
- Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval.
- Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management.
- Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling).
Pay range and compensation package
BeaconFire is an E-verified company and provides equal employment opportunities (visa sponsorship provided).
Equal Opportunity Statement
BeaconFire is committed to diversity and inclusivity.
See all 854+ OPT AI Research Engineer Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship as an AI Research Engineer
Lead with publications and research output
AI Research Engineer hiring managers review your publication record before your resume. List arXiv preprints, conference papers, and workshop contributions prominently. Even one accepted NeurIPS or ICML paper substantially separates you from candidates without published work.
Target STEM-designated roles explicitly
Confirm the role is classified under a STEM CIP code before applying. AI Research Engineer positions typically fall under Computer Science or Electrical Engineering codes, which qualify for the 24-month STEM OPT extension beyond your initial 12 months.
Highlight your E-Verify employer requirement early
STEM OPT extension requires your employer to be E-Verify enrolled. Raise this in early conversations to avoid investing weeks in an interview process with an employer who cannot legally support your extension.
Showcase production-ready research skills
Many labs distinguish researchers who only prototype from those who can deploy. Demonstrate PyTorch or JAX proficiency alongside systems experience. Candidates who bridge research and engineering compress the sponsorship risk employers perceive during OPT periods.
Build a public portfolio of reproducible work
Open-source implementations of your research, well-documented GitHub repositories, and Hugging Face model cards all serve as persistent proof of skill. Hiring teams at research-focused employers frequently review these before extending interview invitations to OPT candidates.
Apply before your OPT start date when possible
Research roles have long hiring cycles, often eight to twelve weeks from first contact to offer. Starting your search three to four months before authorization begins gives employers the runway they need to complete approvals before your start date.
AI Research Engineer OPT: Frequently Asked Questions
Do AI Research Engineer roles qualify for the STEM OPT extension?
Yes, in most cases. AI Research Engineer positions are typically classified under Computer Science or Electrical Engineering CIP codes, both of which qualify for the 24-month STEM OPT extension. You should confirm the specific CIP code on your I-20 matches a STEM-designated field and verify that the employer is E-Verify enrolled before accepting an offer.
How do employers typically view OPT candidates for research engineering roles?
Research-focused employers, including university labs, AI startups, and large technology companies, are generally more comfortable hiring OPT candidates than employers in other industries because they already manage visa sponsorship for international researchers regularly. Your research output, technical depth, and alignment with the team's focus area matter more than your visa status in most screening conversations.
Where can I find AI Research Engineer jobs that are open to OPT candidates?
Migrate Mate filters job listings specifically for visa-sponsored and OPT-friendly roles, so you're not sifting through postings from employers who won't support work authorization. Browsing AI Research Engineer listings on Migrate Mate surfaces positions where sponsorship is already confirmed, which saves significant time during a job search with tight authorization deadlines.
Can I work as an AI Research Engineer on post-completion OPT before my STEM extension is approved?
Yes. You can begin working as soon as your OPT EAD card is valid and your employment is in a role directly related to your degree. You apply for the STEM extension up to 90 days before your initial OPT expires, and USCIS provides a 180-day automatic extension while the application is pending, so your authorization remains continuous.
What does the mandatory training plan requirement mean for AI Research Engineer roles?
During the STEM OPT extension, your employer must complete Form I-983, which outlines how the role provides practical training connected to your degree. For AI Research Engineer positions this is usually straightforward since the work directly involves applying advanced machine learning and computer science skills. Your employer's designated representative signs the plan and is responsible for reporting any material changes to your DSO.