AI Engineer Jobs in Plano, TX
AI Engineer jobs in Plano are concentrated in the Legacy Business Park, Granite Park, and the Shops at Legacy corridor, where telecom, financial services, and enterprise software firms keep steady demand for machine learning, LLM, and MLOps talent. Employers hiring right now include JPMorganChase, Capital One, and onbe. See the openings below and apply to the ones that match your experience.
Find AI Engineer JobsOverview
Open roles360+
Top employerJPMorganChase
Work type50% Hybrid
Top credentialBachelor's degree in statistics
Companies hiring16
Showing 5 of 360+ AI Engineer jobs
AI Engineer III
We won't show you this job again
New 7h ago
Mariner Finance
AI Engineer III
Plano, Texas
New 7h ago
Sr Lead Software Engineer(AI, Data Cloud)
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Added 2d ago
JPMorganChase
Sr Lead Software Engineer(AI, Data Cloud)
Plano, Texas
Added 2d ago
AI Engineer
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Added 3d ago
Fisher Investments
AI Engineer
Plano, Texas
Added 3d ago
Lead Applied AI & Machine Learning Engineer
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Added 5d ago
JPMorganChase
Lead Applied AI & Machine Learning Engineer
Plano, Texas
Added 5d ago
DSML Engineer – Generative AI
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Added 1w ago
LTM Limited
DSML Engineer – Generative AI
Plano, Texas
Added 1w ago
New 7h ago
AI Engineer III
Mariner Finance·Plano, Texas
Job functions:
$134k.98 - $150k/yr
Bachelor's degree in statistics
1,001-5,000 employees
Job Description
Since 1927, the Mariner Finance family of companies has provided customers with creative, flexible, and convenient lending options. Headquartered in Baltimore, Mariner Finance operates coast-to-coast with physical locations in over half the states. With a growing number of employees, superior customer service remains the cornerstone of our business, and we pride ourselves in delivering a variety of loans with an enhanced focus on exceptional service. We work with customers to find options that are beneficial to their specific needs, which is why we are recognized by our customers as one of the community’s consumer finance companies of choice.
Benefits:
For information regarding our benefits, please visit: https://www.marinerfinance.com/careers/benefits/
All full time employees are provided with a generous benefits package in addition to their monetary compensation. Learn more about it today.
In this role, you will...
Be responsible for building and maintaining the knowledge layer and backend services that power enterprise AI agents. Develop the skills and tool registries, knowledge graph components, vector search indexes, data integration pipelines, and agent evaluation suites that help turn standalone models into reliable, governed, tool-using agents.
Partner with Level 4 engineers, the AVP of AI Engineering, Data, Security, and business stakeholders to deliver well-scoped components of the platform. Apply established engineering patterns, contribute to design discussions, and grow technical depth in agentic AI and knowledge engineering.
Responsibilities and Duties:
- Build and maintain components of the enterprise knowledge layer that agents use for grounding, memory, and context, including skills, knowledge graph elements, and vector indexes, working from designs set by senior engineers and contributing improvements.
- Develop and maintain parts of the skills and tool registry, including skill and tool definitions, versioning, discovery, and publishing workflows, and build MCP servers and APIs that expose capabilities to agent builders.
- Implement knowledge graph pipelines, including entity extraction, entity resolution, relationship loading, and schema updates, and build graph and hybrid retrieval queries for agent use cases.
- Build and tune vector search, including embedding generation, semantic chunking, metadata filtering, hybrid search, and index refresh jobs, and measure retrieval quality against agreed metrics.
- Build batch and streaming data pipelines on Databricks (Delta, Spark, Structured Streaming) and modern ETL/ELT patterns to ingest structured, semi-structured, and unstructured data into the knowledge layer, with data quality checks and lineage.
- Build integrations between business systems, document stores, and the knowledge layer using secure REST APIs and connectors. Register and govern data and AI assets through Unity Catalog.
- Implement access controls and entitlement checks in retrieval paths so agents return only data that a given user and agent are permitted to see.
- Build agent evaluation suites, including golden datasets, synthetic test cases, LLM-as-judge and rule-based scorers, and regression tests that measure retrieval quality, groundedness, tool-selection reliability, task completion, safety, latency, and cost.
- Integrate evaluations into CI/CD pipelines as quality gates and review evaluation results to identify regressions and improvement opportunities.
- Write clean, asynchronous, production-ready Python and robust web APIs (such as Flask or FastAPI) that power agent actions and expose knowledge services. Build and integrate agentic tools and workflows for Databricks Custom Agents.
- Apply context and prompt engineering techniques to manage context windows and produce structured outputs (such as JSON schemas) from tool-calling agents.
- Implement monitoring, tracing, and logging for agent loops, tool usage, and retrieval systems, and follow security practices for identity, secrets, runtime isolation, and data store protection.
- Contribute to CI/CD pipelines, test triggers, and multi-environment deployments, deploy services on AWS (including EC2), and use infrastructure as code where available. Participate in code reviews and follow Git branching and merge practices.
- Create and maintain technical documentation, runbooks, and lineage records that support auditability, supportability, and responsible AI governance.
- Troubleshoot and resolve issues in pipelines, retrieval quality, integrations, and agent behavior, escalating complex issues to senior engineers as needed.
- Partner with engineers, data owners, and business stakeholders to understand requirements and deliver reliable components. Learn from code reviews and technical guidance, and share knowledge with peers.
- Perform additional duties as assigned to support evolving business needs.
Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems, or a related field; additional, applicable years of experience may be substituted for a bachelor’s degree.
- Minimum of six (6) years of experience in software engineering, data engineering, platform engineering, machine learning engineering, or a related technology discipline, with hands-on experience in AI, machine learning, or LLM-based solutions (production work, substantial projects, or formal training).
- Strong Python programming skills, including asynchronous programming and testing, and experience building REST APIs (such as Flask or FastAPI).
- Experience building data pipelines using ETL/ELT patterns and SQL, preferably on Databricks or a comparable platform such as Snowflake.
- Working experience with vector databases or vector search, embeddings, chunking strategies, and retrieval-augmented generation (RAG) pipelines.
- Working knowledge of knowledge graphs or graph databases (such as Neo4j, Amazon Neptune, or RDF/SPARQL) and graph or ontology modeling concepts.
- Experience or demonstrated familiarity with building evaluation datasets and automated scoring for LLM or agent outputs.
- Familiarity with agentic tooling, including tool calling, structured outputs, and agent frameworks, and awareness of Model Context Protocol (MCP) or similar tool-integration approaches.
- Familiarity with monitoring, tracing, and logging for applications and distributed services.
- Experience integrating services with business systems through secure APIs, with working knowledge of identity, secrets management, and access control.
- Experience with AWS (including EC2), CI/CD pipelines, and Git branching and code review practices.
- Working knowledge of responsible AI, data privacy, security, and auditability practices.
- Ability to work independently on well-defined tasks, ask for guidance when needed, and collaborate with engineers, data owners, and business partners.
- Strong written and verbal communication skills, with the ability to explain technical work to technical and non-technical audiences.
- Strong analytical thinking and problem-solving ability, with a willingness to learn new tools and techniques quickly.
Preferred Qualifications:
- Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, Engineering, or a related technical discipline.
- Exposure to the Databricks ecosystem, including Mosaic AI Agent Framework, Vector Search, MLflow tracing and evaluation, Databricks SQL, and Unity Catalog.
- Hands-on exposure to agentic frameworks (such as LangGraph or similar), multi-agent coordination, and automated tool calling.
- Exposure to GraphRAG, entity resolution, and graph query languages (such as Cypher, SPARQL, or Gremlin).
- Familiarity with hybrid search, re-ranking, and embedding model evaluation.
- Experience building MCP servers or reusable tool and skill definitions for agents.
- Understanding of model selection, token and inference cost optimization, and embedding models.
- Experience with infrastructure as code (such as Terraform) and containerization (such as Docker).
- Experience with AI or data solutions in a regulated environment such as financial services, banking, lending, or insurance.
Hours of Work:
Work hours will depend on the business hours of the time zone serviced. To the extent permitted by law, the Company may, in its sole discretion, change the work schedule to address business needs.
Physical Demands:
While performing the duties of this job, the employee is frequently required to sit for extended periods; reach with hands and arms; and talk or hear. The employee is occasionally required to move about. The employee must occasionally lift and/or move up to twenty (20) pounds. Specific vision abilities required by this job include close vision and the ability to adjust focus.
EEO:
Mariner Finance is an Equal Opportunity Employer and does not discriminate on the basis of race, color, religion, creed, sex, gender, gender identity or expression, marital status, age, religion, national origin, sexual orientation, familial or caregiver status, citizenship status, status as a victim of domestic violence, medical condition, genetic information, pregnancy, physical or mental disability, or status as a disabled or Vietnam era veteran. Employee must be able to perform the essential duties/functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential duties/functions of their job, absent undue hardship. Drug/Alcohol/Smoke-free workplace.
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Duties, responsibilities, and activities may change or new ones may be assigned at any time or without notice.
Mariner Finance
AI Engineer III
Plano, Texas
New 7h ago1,001-5,000 employees
Job functions:
$134k.98 - $150k/yr
Bachelor's degree in statistics
Job Description
Since 1927, the Mariner Finance family of companies has provided customers with creative, flexible, and convenient lending options. Headquartered in Baltimore, Mariner Finance operates coast-to-coast with physical locations in over half the states. With a growing number of employees, superior customer service remains the cornerstone of our business, and we pride ourselves in delivering a variety of loans with an enhanced focus on exceptional service. We work with customers to find options that are beneficial to their specific needs, which is why we are recognized by our customers as one of the community’s consumer finance companies of choice.
Benefits:
For information regarding our benefits, please visit: https://www.marinerfinance.com/careers/benefits/
All full time employees are provided with a generous benefits package in addition to their monetary compensation. Learn more about it today.
In this role, you will...
Be responsible for building and maintaining the knowledge layer and backend services that power enterprise AI agents. Develop the skills and tool registries, knowledge graph components, vector search indexes, data integration pipelines, and agent evaluation suites that help turn standalone models into reliable, governed, tool-using agents.
Partner with Level 4 engineers, the AVP of AI Engineering, Data, Security, and business stakeholders to deliver well-scoped components of the platform. Apply established engineering patterns, contribute to design discussions, and grow technical depth in agentic AI and knowledge engineering.
Responsibilities and Duties:
- Build and maintain components of the enterprise knowledge layer that agents use for grounding, memory, and context, including skills, knowledge graph elements, and vector indexes, working from designs set by senior engineers and contributing improvements.
- Develop and maintain parts of the skills and tool registry, including skill and tool definitions, versioning, discovery, and publishing workflows, and build MCP servers and APIs that expose capabilities to agent builders.
- Implement knowledge graph pipelines, including entity extraction, entity resolution, relationship loading, and schema updates, and build graph and hybrid retrieval queries for agent use cases.
- Build and tune vector search, including embedding generation, semantic chunking, metadata filtering, hybrid search, and index refresh jobs, and measure retrieval quality against agreed metrics.
- Build batch and streaming data pipelines on Databricks (Delta, Spark, Structured Streaming) and modern ETL/ELT patterns to ingest structured, semi-structured, and unstructured data into the knowledge layer, with data quality checks and lineage.
- Build integrations between business systems, document stores, and the knowledge layer using secure REST APIs and connectors. Register and govern data and AI assets through Unity Catalog.
- Implement access controls and entitlement checks in retrieval paths so agents return only data that a given user and agent are permitted to see.
- Build agent evaluation suites, including golden datasets, synthetic test cases, LLM-as-judge and rule-based scorers, and regression tests that measure retrieval quality, groundedness, tool-selection reliability, task completion, safety, latency, and cost.
- Integrate evaluations into CI/CD pipelines as quality gates and review evaluation results to identify regressions and improvement opportunities.
- Write clean, asynchronous, production-ready Python and robust web APIs (such as Flask or FastAPI) that power agent actions and expose knowledge services. Build and integrate agentic tools and workflows for Databricks Custom Agents.
- Apply context and prompt engineering techniques to manage context windows and produce structured outputs (such as JSON schemas) from tool-calling agents.
- Implement monitoring, tracing, and logging for agent loops, tool usage, and retrieval systems, and follow security practices for identity, secrets, runtime isolation, and data store protection.
- Contribute to CI/CD pipelines, test triggers, and multi-environment deployments, deploy services on AWS (including EC2), and use infrastructure as code where available. Participate in code reviews and follow Git branching and merge practices.
- Create and maintain technical documentation, runbooks, and lineage records that support auditability, supportability, and responsible AI governance.
- Troubleshoot and resolve issues in pipelines, retrieval quality, integrations, and agent behavior, escalating complex issues to senior engineers as needed.
- Partner with engineers, data owners, and business stakeholders to understand requirements and deliver reliable components. Learn from code reviews and technical guidance, and share knowledge with peers.
- Perform additional duties as assigned to support evolving business needs.
Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems, or a related field; additional, applicable years of experience may be substituted for a bachelor’s degree.
- Minimum of six (6) years of experience in software engineering, data engineering, platform engineering, machine learning engineering, or a related technology discipline, with hands-on experience in AI, machine learning, or LLM-based solutions (production work, substantial projects, or formal training).
- Strong Python programming skills, including asynchronous programming and testing, and experience building REST APIs (such as Flask or FastAPI).
- Experience building data pipelines using ETL/ELT patterns and SQL, preferably on Databricks or a comparable platform such as Snowflake.
- Working experience with vector databases or vector search, embeddings, chunking strategies, and retrieval-augmented generation (RAG) pipelines.
- Working knowledge of knowledge graphs or graph databases (such as Neo4j, Amazon Neptune, or RDF/SPARQL) and graph or ontology modeling concepts.
- Experience or demonstrated familiarity with building evaluation datasets and automated scoring for LLM or agent outputs.
- Familiarity with agentic tooling, including tool calling, structured outputs, and agent frameworks, and awareness of Model Context Protocol (MCP) or similar tool-integration approaches.
- Familiarity with monitoring, tracing, and logging for applications and distributed services.
- Experience integrating services with business systems through secure APIs, with working knowledge of identity, secrets management, and access control.
- Experience with AWS (including EC2), CI/CD pipelines, and Git branching and code review practices.
- Working knowledge of responsible AI, data privacy, security, and auditability practices.
- Ability to work independently on well-defined tasks, ask for guidance when needed, and collaborate with engineers, data owners, and business partners.
- Strong written and verbal communication skills, with the ability to explain technical work to technical and non-technical audiences.
- Strong analytical thinking and problem-solving ability, with a willingness to learn new tools and techniques quickly.
Preferred Qualifications:
- Master’s degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, Engineering, or a related technical discipline.
- Exposure to the Databricks ecosystem, including Mosaic AI Agent Framework, Vector Search, MLflow tracing and evaluation, Databricks SQL, and Unity Catalog.
- Hands-on exposure to agentic frameworks (such as LangGraph or similar), multi-agent coordination, and automated tool calling.
- Exposure to GraphRAG, entity resolution, and graph query languages (such as Cypher, SPARQL, or Gremlin).
- Familiarity with hybrid search, re-ranking, and embedding model evaluation.
- Experience building MCP servers or reusable tool and skill definitions for agents.
- Understanding of model selection, token and inference cost optimization, and embedding models.
- Experience with infrastructure as code (such as Terraform) and containerization (such as Docker).
- Experience with AI or data solutions in a regulated environment such as financial services, banking, lending, or insurance.
Hours of Work:
Work hours will depend on the business hours of the time zone serviced. To the extent permitted by law, the Company may, in its sole discretion, change the work schedule to address business needs.
Physical Demands:
While performing the duties of this job, the employee is frequently required to sit for extended periods; reach with hands and arms; and talk or hear. The employee is occasionally required to move about. The employee must occasionally lift and/or move up to twenty (20) pounds. Specific vision abilities required by this job include close vision and the ability to adjust focus.
EEO:
Mariner Finance is an Equal Opportunity Employer and does not discriminate on the basis of race, color, religion, creed, sex, gender, gender identity or expression, marital status, age, religion, national origin, sexual orientation, familial or caregiver status, citizenship status, status as a victim of domestic violence, medical condition, genetic information, pregnancy, physical or mental disability, or status as a disabled or Vietnam era veteran. Employee must be able to perform the essential duties/functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential duties/functions of their job, absent undue hardship. Drug/Alcohol/Smoke-free workplace.
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Duties, responsibilities, and activities may change or new ones may be assigned at any time or without notice.
See All 360+ AI Engineer Jobs in Plano
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Find AI Engineer JobsAI Engineer Job Market in Plano
Who's Hiring
- JPMorganChase146
- Capital One56
- onbe11
- CCS11
- Ericsson11
Top Industries Hiring
- Technology & Software
AI Engineer Jobs in Plano: Frequently Asked Questions
How do I get a ai engineer job in Plano?
Target the large technology and financial services campuses in Legacy Business Park and Granite Park first, as those corridors concentrate the most ai engineer openings in the city. Telecom, fintech, and enterprise SaaS companies dominate local hiring, so experience with production ML systems, cloud platforms like AWS or Azure, and LLM fine-tuning gives you a real edge. Applying directly to Plano employer career portals alongside a curated job board search gets the most traction here.
Which companies hire ai engineers in Plano?
Plano ai engineer roles are posted by JPMorganChase, Capital One, and onbe and others right now, based on current listings on Migrate Mate as of November 2026. Plano attracts a mix of Fortune 500 corporate headquarters, regional tech hubs, and mid-market software companies that maintain sizable AI and data science teams on-site.
Are there remote ai engineer jobs in Plano?
Yes, though availability depends on role type: model research and data pipeline work tends to be more remote-friendly, while roles tied to on-premise infrastructure or regulated financial systems often require on-site presence. About 66% of ai engineer openings tied to Plano are remote or hybrid as of November 2026, reflecting how enterprise tech campuses in Legacy Park and Granite Park handle hybrid arrangements. Roles involving MLOps and cloud deployment are the most consistently offered in hybrid format locally.
How can I get a ai engineer job in Plano with little or no experience?
The most realistic entry path in Plano is through junior data scientist or machine learning analyst roles at the mid-market SaaS and fintech companies along the Legacy corridor, which tend to hire more aggressively at the entry level than the large telecom headquarters nearby. Building a portfolio of deployed projects on GitHub, earning a cloud certification from AWS or Google, and targeting companies with structured rotational programs or dedicated AI teams gives candidates without years of experience a concrete foothold in this market.
Which industries hire the most ai engineers in Plano?
Most ai engineer openings in Plano sit in Technology & Software, per current listings on Migrate Mate as of November 2026. Plano's concentration of telecom and financial services headquarters, combined with a growing cluster of enterprise software firms, creates steady demand for AI talent across model development, automation, and applied analytics functions.
See All 360+ AI Engineer Jobs in Plano
Find roles in Plano that match your experience and apply in just a few clicks.
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