STEM OPT Genai Software Engineer Jobs
GenAI Software Engineer roles sit squarely within STEM OPT eligibility for graduates in computer science, AI, or related CIP-coded fields. Your 24-month STEM OPT extension gives you up to 36 months of total work authorization, provided your employer is enrolled in E-Verify and you maintain a compliant I-983 training plan.
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Get Access To All JobsAt Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.
Position Overview
As a Software Engineer, Professional (GenAI), your role is pivotal in shaping the future of AI-driven business solutions. You will design and develop scalable applications that integrate sophisticated AI models, directly influencing how businesses operate and succeed.
In this role, you will contribute to building next-generation GenAI solutions and automation capabilities, with a focus on embedding risk awareness, controls, and governance into AI-driven systems. Your expertise in Python-based microservices will support the development of robust, quality-controlled frameworks for GenAI solutions, including those supporting governance and approval processes.
By collaborating with GenAI scientists, UX designers, and cross-functional teams, you will help deliver enterprise-grade AI solutions that meet high standards of performance, reliability, and responsible AI practices.
Our Impact
Joining us offers the opportunity to work on cutting-edge GenAI and automation initiatives, gaining hands-on experience in building enterprise-scale AI solutions. You will learn how AI is applied in real-world, regulated environments, and be part of shaping the future of AI-enabled risk management.
Your impact
Key responsibilities include designing and developing scalable GenAI applications such as copilots, automation tools, and workflow solutions, as well as building and enhancing RAG pipelines using vector databases and retrieval strategies. You will apply prompt engineering techniques to improve model performance, develop and maintain Python-based microservices and RESTful APIs, and support the automation of business and risk processes through AI-driven workflows. Additionally, you will contribute to CI/CD pipelines and DevOps practices, assist in implementing guardrails and validation mechanisms for LLM-based applications, and help embed risk and control considerations into AI solutions. Responsibilities also involve data transformation, cleansing, and preparation for AI model usage, ensuring data quality, and supporting model evaluation and continuous improvement. Collaboration with engineers, data owners, product teams, and risk partners is expected, along with participation in code reviews, design discussions, agile ceremonies, and staying current with evolving trends in LLMs, agent frameworks, and AI engineering tools.
Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, IT, or a related field (advanced degree preferred)
- 2–4 years of software development experience
- 1–2 years of hands-on experience in GenAI solutions, including LLMs (e.g., OpenAI, Anthropic, AWS Bedrock)
- Experience building RAG systems using vector databases
- Familiarity with agentic frameworks (e.g., LangChain, LangGraph, or similar)
- 2–4 years of experience in cloud development (AWS preferred), REST APIs, and microservices
- Strong programming skills in Python (experience with TypeScript/Java is a plus)
- Experience building enterprise or customer-facing AI applications
- Familiarity with CI/CD and DevOps practices
- Demonstrated ability to work in cross-functional agile teams
- Exposure to LLM guardrails, evaluation frameworks, or AI safety techniques
- Familiarity with AI governance, model risk, or responsible AI concepts
- Experience supporting quality-controlled or regulated environments
Keys to Success in This Role
- Technical Proficiency: Strong Python skills and ability to build scalable microservices
- Quality & Reliability: Deliver robust, well-tested, and production-ready solutions
- Learning Agility: Continuously develop skills in GenAI and emerging technologies
- Collaboration: Work effectively across engineering, product, and risk teams
- Attention to Detail: Ensure high-quality data, outputs, and system performance
Current Freddie Mac employees please apply through the internal career site.
We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
A safe and secure environment is critical to Freddie Mac’s business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.
CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.
Time-type: Full time
FLSA Status: Non-Exempt
Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.
This position has an annualized market-based salary range of $94,000 - $142,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.
At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.
Position Overview
As a Software Engineer, Professional (GenAI), your role is pivotal in shaping the future of AI-driven business solutions. You will design and develop scalable applications that integrate sophisticated AI models, directly influencing how businesses operate and succeed.
In this role, you will contribute to building next-generation GenAI solutions and automation capabilities, with a focus on embedding risk awareness, controls, and governance into AI-driven systems. Your expertise in Python-based microservices will support the development of robust, quality-controlled frameworks for GenAI solutions, including those supporting governance and approval processes.
By collaborating with GenAI scientists, UX designers, and cross-functional teams, you will help deliver enterprise-grade AI solutions that meet high standards of performance, reliability, and responsible AI practices.
Our Impact
Joining us offers the opportunity to work on cutting-edge GenAI and automation initiatives, gaining hands-on experience in building enterprise-scale AI solutions. You will learn how AI is applied in real-world, regulated environments, and be part of shaping the future of AI-enabled risk management.
Your impact
Key responsibilities include designing and developing scalable GenAI applications such as copilots, automation tools, and workflow solutions, as well as building and enhancing RAG pipelines using vector databases and retrieval strategies. You will apply prompt engineering techniques to improve model performance, develop and maintain Python-based microservices and RESTful APIs, and support the automation of business and risk processes through AI-driven workflows. Additionally, you will contribute to CI/CD pipelines and DevOps practices, assist in implementing guardrails and validation mechanisms for LLM-based applications, and help embed risk and control considerations into AI solutions. Responsibilities also involve data transformation, cleansing, and preparation for AI model usage, ensuring data quality, and supporting model evaluation and continuous improvement. Collaboration with engineers, data owners, product teams, and risk partners is expected, along with participation in code reviews, design discussions, agile ceremonies, and staying current with evolving trends in LLMs, agent frameworks, and AI engineering tools.
Qualifications
- Bachelor’s degree in Computer Science, Computer Engineering, IT, or a related field (advanced degree preferred)
- 2–4 years of software development experience
- 1–2 years of hands-on experience in GenAI solutions, including LLMs (e.g., OpenAI, Anthropic, AWS Bedrock)
- Experience building RAG systems using vector databases
- Familiarity with agentic frameworks (e.g., LangChain, LangGraph, or similar)
- 2–4 years of experience in cloud development (AWS preferred), REST APIs, and microservices
- Strong programming skills in Python (experience with TypeScript/Java is a plus)
- Experience building enterprise or customer-facing AI applications
- Familiarity with CI/CD and DevOps practices
- Demonstrated ability to work in cross-functional agile teams
- Exposure to LLM guardrails, evaluation frameworks, or AI safety techniques
- Familiarity with AI governance, model risk, or responsible AI concepts
- Experience supporting quality-controlled or regulated environments
Keys to Success in This Role
- Technical Proficiency: Strong Python skills and ability to build scalable microservices
- Quality & Reliability: Deliver robust, well-tested, and production-ready solutions
- Learning Agility: Continuously develop skills in GenAI and emerging technologies
- Collaboration: Work effectively across engineering, product, and risk teams
- Attention to Detail: Ensure high-quality data, outputs, and system performance
Current Freddie Mac employees please apply through the internal career site.
We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
A safe and secure environment is critical to Freddie Mac’s business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.
CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.
Time-type: Full time
FLSA Status: Non-Exempt
Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.
This position has an annualized market-based salary range of $94,000 - $142,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.
See all STEM OPT Genai Software Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Genai Software Engineer Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as a Genai Software Engineer
Verify your CIP code before applying
Check that your degree's Classification of Instructional Programs code maps to a DHS-designated STEM field. Computer science, data science, and electrical engineering codes qualify. A mismatch between your transcript and your I-20 can block the extension before it starts.
Confirm E-Verify enrollment before accepting offers
Ask hiring managers directly whether the company is enrolled in E-Verify before you reach the offer stage. STEM OPT authorization requires it, and smaller GenAI startups frequently aren't enrolled yet, even if they're willing to sponsor.
Build an I-983 training plan around GenAI deliverables
Your I-983 must tie your GenAI work to specific learning objectives and your degree field. Document model development, fine-tuning pipelines, or RAG architecture work as concrete training goals. Vague job descriptions get flagged by DSOs and can delay your extension.
Use OFLC Wage Search to benchmark your offer
GenAI Software Engineer roles span multiple SOC codes, each with a different prevailing wage. Run your job title and work location through the OFLC Wage Search to confirm your offer meets at least the Level I wage. An underpaid offer can complicate future H-1B visa sponsorship.
Target employers with H-1B filing history on Migrate Mate
Search GenAI Software Engineer roles on Migrate Mate to see which employers have active DOL Labor Condition Application filing history. Companies that already file LCAs understand visa timelines and are far more likely to support your OPT-to-H-1B transition without hesitation.
Time your extension filing to protect cap-gap coverage
Submit your STEM OPT extension application to USCIS at least 90 days before your initial OPT EAD expires. If you're also in an H-1B lottery year, a timely filing preserves your cap-gap work authorization through October 1 even if USCIS hasn't adjudicated your I-765 yet.
Frequently Asked Questions
Does a GenAI Software Engineer role qualify for the STEM OPT extension?
Yes, if your degree is in a DHS-designated STEM field such as computer science, data science, or electrical engineering and the role directly applies that training. The job title alone doesn't determine eligibility. Your DSO reviews the I-983 training plan to confirm the work aligns with your degree's CIP code. Roles focused on large language model development, fine-tuning, or AI infrastructure typically satisfy this alignment requirement.
What E-Verify requirement applies to my STEM OPT employer?
Your employer must be enrolled in E-Verify before you can be authorized to work under the STEM OPT extension. This is a federal requirement enforced by ICE. Enrollment isn't the same as simply using E-Verify for one hire. Ask the recruiter or HR team for the company's E-Verify employer ID to confirm active enrollment before you sign an offer letter.
What goes into the I-983 training plan for a GenAI role?
The I-983 requires you and your employer to document specific learning objectives tied to your STEM degree, the supervision structure, and how the role develops your skills. For GenAI positions, this means describing concrete technical work such as training pipelines, prompt engineering, model evaluation, or deployment infrastructure. Generic descriptions like 'software development' aren't sufficient. USCIS guidance requires objectives specific enough to evaluate whether training goals are being met.
How does cap-gap work if I'm on STEM OPT and selected in the H-1B lottery?
If you file a timely H-1B petition before your STEM OPT EAD expires and USCIS receives it by the cap-gap start date, your work authorization automatically extends through September 30. If your H-1B petition is approved with an October 1 start date, you're covered continuously without a gap. If your petition is denied, your STEM OPT authorization ends and you enter a 60-day grace period. USCIS publishes cap-gap guidance on its OPT pages.
Where can I find GenAI Software Engineer jobs with E-Verify employers?
Migrate Mate filters GenAI Software Engineer listings to show employers with verified E-Verify enrollment and active DOL Labor Condition Application filing history, so you're not wasting applications on companies that can't legally hire you under STEM OPT. You can search by role, location, and employer filing history to prioritize companies already familiar with OPT and H-1B sponsorship workflows.