Ai Agent

Ai Agent Data Jobs

66 jobs found

Today

Principal Machine Learning Engineer

Okta San Francisco, CA

San Francisco, CA

Today

$238k - $326k/yr Full time Backend Developer Agentic Ai Ai Agent

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Job Description

Okta is hiring a Principal Machine Learning Engineer (Okta Secures AI) to evolve authorization for agent access policies using dynamic AI security mechanisms.

Responsibilities

Build intent-based enforcement to confirm agent runtime requests match intended purpose
Apply LLM reasoning and prompt parsing to interpret prompts, tool payloads, and intent in real time
Integrate low-latency inference or semantic evaluation engines into the API gateway request path
Use embeddings, vector search, or zero-shot classification to score alignment between agent intent and executed actions
Design confidence-scored decision engines that feed semantic verification results into policy frameworks such as Cedar
Establish evaluation benchmarks, prompt injection defenses, and guardrails to prevent bypasses or false positives
Architect scalable ML and Generative AI systems with retrieval, inference, and evaluation pipelines
Optimize prompting, context retrieval, and RAG workflows for accuracy, safety, and efficiency in Claude-based systems
Build automated evaluation pipelines to measure model quality, correctness, groundedness, and safety in production
Implement schema validation, structured output enforcement, and guardrails for reliable, compliant AI outputs
Mentor and coach engineers to support team and community growth

Requirements

10+ years of software development experience with strong Python expertise; Go or TypeScript familiarity is a plus
Hands-on experience with applied machine learning, including feature engineering, training, and fine-tuning models
Hands-on experience with modern Generative AI platforms such as AWS Bedrock, OpenAI, Anthropic, etc.
Deep understanding of retrieval-augmented generation (RAG), embeddings, and knowledge-base workflows
Hands-on experience with AI agent frameworks including LiteLLM, LangGraph, LangChain, LlamaIndex, MCP, or similar
Familiarity with ML frameworks such as FastAPI, PyTorch, TensorFlow, and Spark ML, plus orchestration tools like Airflow
Experience defining evaluation metrics, pipelines, and feedback loops for ML/GenAI systems
Proven ability to collaborate with product and engineering teams to drive greenfield initiatives, manage unknowns, and iterate quickly
Experience building tools or infrastructure for AI/ML applications with deep understanding of the developer lifecycle in an AI-native world

Technologies

Python, Go, TypeScript
AWS Bedrock, OpenAI, Anthropic
LiteLLM, LangGraph, LangChain, LlamaIndex, MCP
FastAPI, PyTorch, TensorFlow, Spark ML
Airflow, Cedar
Claude-based systems

Location & Salary

San Francisco, CA (hybrid)
USD 238,000 - 326,000 per yearly

Education

Bachelor’s or Master’s degree in Computer Science or related field

Benefits

Equity (where applicable), bonus, and benefits including health, dental and vision insurance
401(k)
Flexible spending account
Paid leave including PTO and parental leave

Extra Credit

Experience integrating AI-driven systems with identity, authentication, or security products
Exposure to ethical AI, model risk, or compliance frameworks
Familiarity with evaluation datasets, synthetic data generation, or LLM-as-a-judge methods

Okta Experience

Supporting Your Well-Being
Driving Social Impact
Developing Talent and Fostering Connection + Community

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Today

Senior Machine Learning Engineer, Developer AI

ByteDance San Jose, CA

San Jose, CA

Today

$218k - $480k/yr Full time Python Agentic Ai Ai Agent

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Job Description

ByteDance’s Dev Infra team is hiring a Senior Machine Learning Engineer to support the Dev AI initiative. The focus is on building intelligent systems that help software engineering teams work at scale, including AI for code generation, automated testing, debugging, code understanding, and agentic software engineering.

What You’ll Do

Develop and improve machine learning and large language model systems for software engineering tasks, including code generation, unit test generation, and debugging.
Build AI-powered developer agents and intelligent workflows that can reason over large codebases, operate with development environments and tools, execute multi-step engineering tasks, and support engineers across the software development lifecycle.
Enhance model and agent performance using prompt engineering, context engineering, retrieval, fine-tuning, reinforcement learning, tool-use design, and agent harness engineering.
Create training and evaluation data pipelines for software engineering tasks, including data collection, filtering, synthesis, labeling, and hard-example mining.
Apply advances in large language models, code intelligence, program analysis, reinforcement learning, and autonomous software engineering to address real developer productivity needs at scale.

Requirements

Bachelor’s degree or above in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
5+ years of relevant industry or research experience in machine learning, large language models, code intelligence, AI-powered developer tools, or related areas.
Strong programming skills in one or more languages such as Python, Go, Java, C++, JavaScript, or TypeScript.
Solid understanding of data structures, algorithms, machine learning, operating systems, databases, and fundamental system design principles.
Experience owning complex machine learning projects end-to-end, from problem formulation and data construction to model development, evaluation, deployment, and production iteration.
Strong system design and engineering skills, including building scalable, reliable, and efficient machine learning systems or AI-powered applications.
Strong communication and collaboration skills, including driving complex technical projects across teams.

Technologies

Python
Go
Java
C++
JavaScript
TypeScript

Preferred Qualifications

Experience building or leading AI systems for software engineering, including code generation, coding agents, unit test generation, debugging, or code review.
Deep experience with large language models and one or more model improvement or post-training techniques, such as supervised fine-tuning, reinforcement learning, preference optimization, prompt engineering, context engineering, retrieval, or model evaluation.
Experience designing and improving agentic systems, including tool-using LLMs, coding agents, agent harnesses, MCP, agent skills, planning, memory, or multi-step execution workflows.
Experience building large-scale training data, evaluation datasets, benchmarks, or experimentation pipelines for machine learning or code intelligence systems.
Strong understanding of software engineering and code intelligence techniques such as program analysis, compilers, static analysis, code search, repository indexing, testing, and debugging.
Publications, patents, open-source contributions, or demonstrated technical leadership in machine learning, large language models, code intelligence, developer tools, or AI for software engineering.

Compensation

Salary: USD 218,400 - 480,000 per year (base salary range for the selected city).

Location and Work Setup

Location: San Jose, CA
Onsite: Yes

Benefits

Day one access to medical, dental, and vision insurance
401(k) savings plan with company match
Paid parental leave
Short-term and long-term disability coverage
Life insurance
Wellbeing benefits
10 paid holidays per year
10 paid sick days per year
17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)
Additional discretionary bonuses/incentives and restricted stock units (role may be eligible)

Reasonable Accommodation

ByteDance is committed to providing reasonable accommodations in its recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs, or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, reach out at https://tinyurl.com/RA-request.

Equal Opportunity / Fair Chance (Los Angeles County Unincorporated)

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. ByteDance notes that criminal history may have a direct, adverse, and negative relationship on job duties, potentially resulting in the withdrawal of a conditional offer of employment, including interacting with internal or external clients or colleagues, handling confidential information, and exercising sound judgment.

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Today

Machine Learning Engineer, Search and Shopping

Google Mountain View, CA

Mountain View, CA

Today

$207k - $300k/yr Full time Ad Tech Agentic Ai Ai Agent

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Job Description

Google is hiring a Machine Learning Engineer to help power Search and Shopping Ads. The role centers on building and scaling low-latency predicted click-through rate (pCTR) models, then integrating ads into emerging AI search experiences while meeting tight compute and return-on-investment constraints.

Based in Mountain View, CA with onsite work, you will partner closely across Ads Machine Learning and research groups, including DeepMind, to design architectures and training methods that translate user signals and auction objectives into production improvements.

Role focus

Lead the technical architecture, delivery, and cross-team strategy for Search and Shopping Ads pCTR models in partnership with DeepMind, Research, and Ads Machine Learning teams.
Design, prototype, and scale high-capacity pCTR architectures that maximize Tensor Processing Unit (TPU) capabilities while operating under strict low-latency serving and return-on-investment budgets.
Develop modeling solutions that capture deep user history and nuanced attention signals, integrating ads into emerging AI Search experiences such as AI Overviews and AI Mode.
Engineer loss functions and calibration methods to convert complex business and auction objectives into measurable metric and auction improvements.
Build agentic machine learning workflows that automate and accelerate optimal model architecture and feature space discovery.

About the job

Invent novel low-latency architectures that evaluate layouts in milliseconds while maximizing TPU capabilities.
In close collaboration with DeepMind and Research, design sequence modeling to capture deep user history across modern experiences like Artificial Intelligence Overviews and Artificial Intelligence Mode.
Engineer loss functions for auction dynamics and deploy agentic AI workflows to accelerate model discovery.

Required qualifications

Bachelor’s degree or equivalent practical experience.
8 years of experience with software development, including 5 years with large-scale machine learning, deep learning, neural networks, or recommendation systems.
Experience designing and implementing large-scale production deep learning or neural network architectures under latency and computational constraints.
Experience leading cross-functional technical projects and mentoring other engineers.

Preferred qualifications

PhD degree in Computer Science, Machine Learning, Artificial Intelligence, or related fields.
Experience with agent-driven ML exploration, hyperparameter tuning, or automated model architecture search.
Experience with one or more of: loss engineering for business objectives, joint modeling across distinct prediction stacks, or hardware-aware ML optimizations (for example, leveraging dense compute/TPUs effectively).
Familiarity with ads prediction systems, auction dynamics, or serving infrastructure (such as AdBrain or Admixer).
Ability to collaborate with peer technical leads and advanced ML research organizations (such as DeepMind or Google Research) to bring academic or exploratory work into production.

Technologies

Tensor Processing Unit (TPU)
Large-scale machine learning, deep learning, neural networks
Recommendation systems
Sequence modeling
Agentic artificial intelligence workflows / agentic machine learning workflows
Loss functions, calibration methods

Compensation and benefits

US salary range: $207,000 - $300,000 (USD) per year
20% bonus target + equity + benefits
Learn more about benefits at Google.

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Today

Senior Machine Learning Engineer

Unity Technologies SF Mountain View, CA

Mountain View, CA

Today

$210k - $273k/yr Full time Senior Agentic Ai Ai Agent

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Job Description

Unity Technologies SF is hiring a Senior Machine Learning Engineer to help build foundational agentic AI systems inside the Unity engine. This onsite role in Mountain View, CA focuses on designing, scaling, and integrating AI agent systems and models for real-time games and simulations, including planning, memory and world modeling, and ML/AI safety.

You will work on systems that support goal-directed behavior, task planning and execution, and environment-aware decision-making. The role also emphasizes technical leadership: you will drive high-impact initiatives, help define long-term direction for Unity’s agentic AI offerings, and mentor engineers and researchers while strengthening a culture of innovation, excellence, and collaboration.

What you’ll do

Design, implement, and scale AI agent systems in Unity environments to enable goal-directed behavior, task planning and execution, and environment-aware decision-making.
Build reusable agentic frameworks such as planning modules, memory systems, or policy adaptation layers that creators can extend in their own projects.
Develop AI models for Unity’s AI agentic system to support tasks involved in building Unity games.
Integrate ML models within real-time game engine constraints, optimizing for latency, compute, and determinism.
Lead major initiatives, including hierarchical reinforcement learning for scalable behaviors, AI planning and goal inference for NPCs and simulations, and agent memory and world modeling for persistent, believable behavior.
Collaborate with internal and external teams to expand use cases across gaming, simulation, and interactive storytelling.
Contribute to Unity’s agentic AI roadmap, ensuring modularity, usability, and performance across platforms.
Establish and champion best practices for model quality, simulation-based evaluation, and ML/AI safety within real-time systems.
Mentor engineers and researchers, supporting a technical culture of innovation, excellence, and collaboration.

What you bring

MS or Ph.D. in Computer Science, Machine Learning, Robotics (or equivalent practical experience).
5+ years of hands-on experience developing ML systems in production, ideally in real-time or interactive environments.
A strong background in one or more of the following: reinforcement learning, fine-tuning, decision-making under uncertainty, AI planning, or multi-agent systems.

Compensation and location

Location: Mountain View, CA (onsite)

Salary: USD 210,300 to 273,400 per year

Benefits

Comprehensive health, life, and disability insurance
Commute subsidy
Employee stock ownership
Competitive retirement/pension plans
Generous vacation and personal days
Support for new parents through leave and family-care programs
Office food snacks
Mental Health and Wellbeing programs and support
Employee Resource Groups
Global Employee Assistance Program
Training and development programs
Volunteering and donation matching program

English communication requirement

This position requires the incumbent to have sufficient knowledge of English, including frequent and regular communication with colleagues and partners worldwide whose common language is English.

Privacy

For application details, review the Prospect and Applicant Privacy Policies. Contact: DPO@unity.com

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Today

Principal AI Engineer (SDLC)

AT&T Dallas, TX

Dallas, TX

Today

Full time Backend Developer Agentic Ai Ai Agent

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Job Description

AT&T seeks a Principal AI Engineer to design, build, and deploy production-ready generative AI and enterprise applications across the full SDLC.

Responsibilities

Design, develop, and deploy AI-powered applications and platforms aligned to enterprise business objectives
Build generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based workflows
Develop intelligent assistants including copilots, chatbots, and AI automation solutions to improve employee and customer experiences
Turn AI concepts, proofs of concept, and prototypes into production-ready software products
Design and build scalable APIs, microservices, and backend services powering AI-enabled applications
Integrate AI capabilities into existing enterprise platforms, business systems, and customer-facing applications
Develop secure, reliable, and reusable application components within modern software architectures
Partner with cross-functional teams to translate business requirements into technical solutions
Deploy and manage AI workloads across cloud environments including Azure and AWS
Implement containerized and cloud-native solutions using Kubernetes and modern orchestration technologies
Build and maintain enterprise-grade AI platforms designed for high-volume production workloads
Optimize performance, reliability, security, and scalability of AI services
Establish and maintain CI/CD pipelines for AI-enabled applications and services
Apply MLOps best practices for deployment, monitoring, testing, and lifecycle management of AI solutions
Support model integration, version management, governance, and operational excellence
Monitor production environments and continuously improve platform performance and user experience
Evaluate emerging AI technologies and identify opportunities for enterprise adoption
Collaborate with product managers, software engineers, data scientists, UX teams, and business stakeholders
Contribute to technical architecture decisions and AI engineering best practices
Drive continuous improvement across AI development methodologies and delivery frameworks

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field
Experience developing enterprise applications using modern software engineering practices
Strong proficiency in Python and modern application development frameworks
Experience building RESTful APIs and microservices
Knowledge of generative AI technologies including LLMs and AI application architectures
Experience with cloud platforms such as Azure and/or AWS
Experience working within Agile and SDLC environments
Knowledge of CI/CD pipelines, DevOps practices, and software release management
Experience with containerization and orchestration technologies such as Kubernetes and Docker
Strong problem-solving, analytical, and collaboration skills

Technologies

Python
RESTful APIs
microservices
Large Language Models (LLMs)
Generative AI
Retrieval-Augmented Generation (RAG)
agent-based workflows
Azure
AWS
Kubernetes
Docker
CI/CD pipelines
DevOps
MLOps
Agile
SDLC
vector databases
prompt engineering
AI evaluation frameworks
MLOps platforms
machine learning deployment practices

Example projects

Enterprise generative AI chatbots and virtual assistants
AI-powered recruiting and talent acquisition solutions
Customer care AI assistants powered by GPT and LLM technologies
Retrieval-Augmented Generation (RAG) platforms
Multi-agent and agentic workflow automation systems
AI APIs and shared enterprise AI services
AI-enabled operational intelligence and analytics platforms

Example at AT&T

Build a Network Operations Copilot that leverages multiple LLMs
Integrate with trouble-ticket and operational systems
Provide intelligent outage recommendations
Surface network analytics and operational insights
Deliver a fully deployed, production-ready software solution

Preferred qualifications

Experience building RAG (Retrieval-Augmented Generation) solutions
Experience developing agentic AI workflows and autonomous AI systems
Knowledge of MLOps platforms and machine learning deployment practices
Experience integrating AI solutions into enterprise business systems
Familiarity with vector databases, prompt engineering, and AI evaluation frameworks
Experience developing scalable cloud-native AI applications
Exposure to enterprise security, governance, and responsible AI practices

Ideal background

Candidates may currently hold titles such as AI Engineer, Generative AI Engineer, Machine Learning Engineer, AI Solutions Engineer, AI Application Engineer, or AI Platform Engineer

Location and schedule

Dallas, TX onsite
Location listing includes: Atlanta, Georgia and Dallas, Texas
Weekly hours: 40
Time type: Regular

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Today

AI Engineer

SOLIDWORKS Waltham, MA

Waltham, MA

Today

Full time Backend Developer Python Agentic Ai

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Job Description

Join SOLIDWORKS in Waltham, MA to build AI agents that connect directly with SolidWorks and help automate complex engineering workflows. This role focuses on turning multi-step reasoning into working CAD operations, from sketch creation to 3D model generation, and integrating those agents into design pipelines.

What you will do

Design and develop AI agents that can interact with SolidWorks through its APIs.
Create multi-step reasoning workflows where agents parse instructions, plan tasks, and execute CAD operations.
Integrate AI agents into client-server architectures using communication protocols such as WebSocket, REST, or similar approaches.
Implement automated generation of sketches and 3D models.
Debug, optimize, and improve agent workflows to ensure robust and accurate outputs.
Evaluate agent performance, tune prompts, and work to reduce hallucinations in structured engineering tasks.
Collaborate with mechanical engineers, UI/UX developers, and product definition to shape AI agentic workflows and implement them.

Requirements

Bachelor’s or Master’s Degree in Computer Science Engineering, IT, or a related engineering stream.
2–5 years of experience using C#, C++, Python, and AI technologies.
A solid understanding of software engineering principles and object-oriented programming.
Familiarity with CAD, visualization, simulation, or content creation applications (beneficial).
Interest or experience in AI/ML technologies for graphics, rendering, image generation, or workflow automation (plus).
Knowledge of other scripting languages is a plus.

Technologies

C#, C/C++, Python
LLMs, Embeddings, vector search, RAG systems
Agent frameworks (multi-step reasoning, tool use)
LangChain or LlamaIndex
OpenAI / Gemini / Claude APIs
Visual Studio, Git, Azure DevOps, Jira
WebSocket, REST
Cursor, VS Code

Benefits

Choice of plans providing comprehensive coverage for medical, dental, and vision for employee and dependents
Employee life
Short- and long-term disability
Tuition reimbursement
Immediate 401K enrollment
401K match: 50 cents on the dollar, up to the first 8% of eligible compensation (based on match eligibility criteria)
Flexible time off policy
10 paid holidays

Location: Waltham, MA (onsite)

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Today

AI Engineer, Ontologies & Knowledge Graphs

Cadence Design Systems Livonia, MI

Livonia, MI

Today

Full time Backend Developer Agentic Ai AI

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Job Description

Cadence Design Systems is seeking an AI Engineer to build knowledge graphs and retrieval-ready data pipelines that help make product capabilities programmatically understandable.

Responsibilities

Develop ETL/ELT pipelines to extract data from source code, APIs, file formats, and documentation and load it into a structured knowledge store
Design and maintain schemas and semantic data models for entities, relationships, and capabilities
Build and maintain knowledge graphs across heterogeneous product data
Create and maintain source and metadata parsers, including source-code/AST parsing for automated structure extraction
Implement typed programmatic interfaces and data-access layers on top of the knowledge layer
Deliver retrieval and indexing layers over product knowledge using embeddings and RAG
Partner with domain engineers to break complex product workflows into discrete, callable operations
Evaluate data sources for coverage, quality, and schema completeness across multiple products

Requirements

BS/MS in Computer Science, Mechanical Engineering, or similar
Strong Python and experience building and consuming REST APIs
Experience building data pipelines (ETL/ELT) across structured and unstructured data
Familiarity with graph databases and/or semantic/ontology modeling (RDF, OWL, property graphs, or equivalent)
Experience with at least one agent framework: LangChain, LangGraph, AutoGen, CrewAI, or similar
Understanding of how LLMs use context and call tools (retrieval, RAG, embeddings)
Exposure to CAE/FEA/CFD or a related physical-simulation or engineering domain
Comfortable working within unfamiliar or undocumented codebases
Systems thinking skills to decompose legacy workflows into discrete, callable steps

Technologies

Python, REST APIs, ETL/ELT
Graph databases; RDF, OWL, property graphs
LangChain, LangGraph, AutoGen, CrewAI
LLMs, retrieval, RAG, embeddings
CAE/FEA/CFD
AST parsing

Nice to Have

Vector databases
Data-access and API interface development
Parsing structured file formats
Surrogate modeling or related numerical methods

Additional Information

Role spans multiple products, building structured knowledge and interfaces over their capabilities
Works closely with domain engineers, who provide subject-matter expertise
Travel is not an expectation; occasional infrequent travel may occur for broad team alignment workshops