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Masters Artificial Intelligence Jobs (NOW HIRING)

Artificial Intelligence and/or Machine Learning technologies applied to space systems * System ... Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience ...

The Senior AI & Data Science job plans and leads the development of artificial intelligence models ... Masters degree or PhD in Applied Mathematics, Computer Science, Data Science, Operations Research ...

ORA_ON_SITE Description SAIC seeks an Artificial Intelligence/Machine Learning Systems Engineer to ... Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience ...

... artificial intelligence platform and we are looking for data science interns in the areas of ... Masters/PhD preferred. Ideally we would like to see someone that has been published in Natural ...

AI/ML Systems Engineer

Chantilly, VA · On-site

$160K - $200K/yr

ORA_ON_SITE Description SAIC seeks an Artificial Intelligence/Machine Learning Systems Engineer to ... Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience ...

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Masters Artificial Intelligence information

What types of projects or problems do professionals with a Master's in Artificial Intelligence typically work on within organizations?

Professionals with a Master's in Artificial Intelligence often work on a wide range of projects, such as developing machine learning models for predictive analytics, designing intelligent automation systems, and improving natural language processing capabilities. They frequently collaborate with data scientists, software engineers, and domain experts to address real-world challenges like fraud detection, personalized recommendations, and process optimization. These roles require both technical expertise and the ability to translate complex data insights into actionable business solutions, providing ample opportunities for innovation and cross-functional teamwork.

What are the key skills and qualifications needed to thrive as a Master’s-level Artificial Intelligence professional, and why are they important?

To thrive in an Artificial Intelligence role at the master's level, you need strong expertise in machine learning, programming (such as Python or R), and a solid foundation in mathematics and statistics, typically supported by an advanced degree in AI, computer science, or a related field. Familiarity with AI frameworks (like TensorFlow or PyTorch), cloud platforms, and relevant certifications (such as AWS Certified Machine Learning) are often required. Critical thinking, problem-solving, and effective communication are essential soft skills for turning data-driven insights into actionable solutions. These skills and qualifications are vital for developing innovative AI systems that address complex real-world challenges and drive organizational success.

What is the difference between Masters Artificial Intelligence vs Data Scientist?

AspectMasters Artificial IntelligenceData Scientist
Required CredentialsMaster's degree in AI, Computer Science, or related fieldMaster's degree in Data Science, Statistics, or related field
Work EnvironmentResearch labs, tech companies, AI development teamsBusiness analytics, data analysis, and modeling teams
Industry UsageAI research, machine learning development, automationData analysis, predictive modeling, business insights

Masters Artificial Intelligence and Data Scientist roles share overlapping skills and educational backgrounds, but AI focuses more on developing intelligent systems and algorithms, while Data Scientists analyze data to generate insights. Both roles are in high demand across tech and industry sectors, often requiring advanced degrees and similar technical skills.

What are Masters in Artificial Intelligence?

A Masters in Artificial Intelligence is a graduate-level degree program that focuses on the theory, development, and application of AI technologies. Students in these programs learn about machine learning, deep learning, natural language processing, robotics, and data science. The curriculum often combines computer science fundamentals with hands-on projects and research opportunities. Graduates are prepared for roles in industries like technology, healthcare, finance, and research, where AI skills are in high demand.
Infographic showing various Masters Artificial Intelligence job openings in the United States as of July 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
Sr Lead Software Engineer - Artificial Intelligence

Sr Lead Software Engineer - Artificial Intelligence

JP Morgan Chase

Plano, TX • On-site

Full-time

Medical, Retirement

Posted 5 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 492 frontline employees who took The Breakroom Quiz

60th of 150 rated banks


Job description

Build and operate the AI toolchain that is accelerating mainframe modernization at scale.

As an Sr Lead Software Engineer within Core Processing, Wealth Management Technology, you will design, build, and ship the agentic systems that ingest decades of mainframe logic and produce verified, production-ready modern services. You work directly alongside domain SMEs and the ED lead to turn legacy COBOL, JCL, DB2, and batch schedules into structured specifications - then drive those specs through agent-accelerated delivery into the target platform. You are a builder first: comfortable architecting multi-agent orchestration one day and debugging a prompt chain against production edge cases the next. You have deep proficiency extending and operating coding agents (Claude Code, Codex, Copilot), and you bring the engineering rigor to make AI outputs reliable at enterprise scale. You thrive on hard problems, move fast, and care deeply about shipping software that works.

Job Responsibilities

  • Builds and operates the spec generation pipeline - Implement artifact ingestion (COBOL source, JCL, job schedules, DB2 schemas, SME-captured knowledge), chunking strategies, and RAG pipelines that produce structured calculation and workflow specifications validated by domain experts.
  • Develops agentic workflows for code translation and migration - Design, implement, and iterate on multi-agent systems that translate legacy logic into target-state code (Kotlin/JVM). Build orchestration layers, tool-use patterns, and guardrails that ensure output correctness for financial calculations.
  • Builds evaluation and verification infrastructure - Create automated test harnesses that compare migrated calculation outputs against legacy results. Implement parity testing frameworks, regression suites, and confidence scoring to gate production cutover decisions.
  • Contributes to the standard calculation runtime - Help build and extend the target platform that migrated calculations deploy into. Ensure the runtime supports deterministic, immutable, auditable execution.
  • Partners with domain SMEs - Embed with mainframe subject-matter experts across Credit, Money Market & Mutual Funds, Statements & Tax, and IBOR to validate agent outputs, refine prompt strategies, and close knowledge gaps in specifications.
  • Extends ETL and CDC pipelines for agent workflows - Build and integrate event sourcing, CDC (change data capture), and data pipelines that support end-to-end migrated workflows, including upstream/downstream dependency mapping.
  • Operates AI systems in production - Own LLMOps for the toolchain: deployment, monitoring, cost management, latency optimization, token budget management, and incident response. Ensure reliability and compliance for 24/7 operation.
  • Iterates rapidly and ships continuously - Work in tight build-measure-learn cycles. Prototype quickly, instrument everything, and make data-driven decisions about agent architectures, model selection, and prompt strategies.
  • Contributes to shared tooling and infrastructure - Build reusable libraries, evaluation harnesses, prompt templates, and orchestration patterns that scale AI capabilities across all four core processing domains.

Required Qualifications, Capabilities, and Skills

  • 5+ years of software engineering experience shipping production systems
  • 2+ years of hands-on experience building LLM-based applications - agentic architectures, RAG pipelines, prompt engineering, and evaluation frameworks
  • Strong software engineering fundamentals: distributed systems, event-driven architectures, API design, testing practices, and cloud platforms (AWS/EKS/ECS)
  • Expert proficiency with AI-assisted development tools (Claude Code, GitHub Copilot, Cursor) as core daily workflow
  • Experience with at least one of: Kotlin/JVM(Java), Python, Rust in production environments
  • Demonstrated ability to operate and debug complex systems 
  • Clear communicator who can articulate technical trade-offs to both engineers and business stakeholders
  • Experience with code migration.

Preferred Qualifications, Capabilities, and Skills

  • Experience with legacy systems, mainframe technologies (COBOL, JCL, DB2), or large-scale migration programs
  • Familiarity with workflow orchestration (Temporal, Airflow) and event sourcing / CDC patterns
  • Experience with Kafka, PostgreSQL, and container orchestration (Kubernetes/EKS)
  • Background in financial services, wealth management, brokerage, or capital markets processing
  • Experience building code analysis, translation, or verification tooling
  • Masters in Computer Science or equivalent experience

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

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