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3 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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1mo ago

Machine Learning Engineer

GitHub, Inc. Remote 📍 United States Remote

Remote

1mo ago Closed

$108k - $286k/yr Full time Agentic Ai Ai Enabled Security Ai Security

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

GitHub, Inc. is hiring an experienced Machine Learning Engineer to design, build, and deploy agentic LLM-based solutions that help detect and prevent fraud, abuse, and security threats across GitHub at scale. The role also involves identifying vulnerabilities tied to abuse, performing ad-hoc analysis, and assessing the impact of safety and integrity initiatives.

Responsibilities

Design, build, and deploy agentic solutions using large language models for large-scale detection and prevention of fraud, abuse, and security threats, including content classification and multi-step agentic investigations.
Build production-grade systems that operate reliably against high-volume event streams, leveraging AI coding assistants to accelerate and improve development.
Develop and operate scalable machine learning systems on cloud platforms, including Azure AI Foundry, to train, deploy, and serve models and agentic solutions in production.
Evaluate and improve existing models and agentic solutions through offline evaluations, including tool-use loops and LLM-as-judge evaluation, along with performance metrics and feedback from operational deployments.
Identify vulnerabilities in products that can lead to abuse and consult with product teams during reviews of new features.
Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and content moderators, to integrate agentic solutions into production systems.
Document the systems you help build and support the technical growth of peers.

Requirements

4+ years of experience in machine learning or a related field; or a Bachelor’s degree in Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or a related field plus 2+ years of machine learning experience; or a Master’s degree in Machine Learning or related fields; or equivalent experience.
Strong understanding of large language models, including hands-on experience applying them at scale, ideally for classification and agentic workflows or agents.
Strong software engineering skills, including experience building with AI coding assistants.
Experience designing or evaluating agentic systems, such as tool-use loops, multi-step workflows, or LLM-as-judge evaluation.
Hands-on experience building and operating classification or detection systems at scale, including work with imbalanced data and precision/recall tradeoffs.
Experience in Trust and Safety, National Security, or fighting spam, malware, fraud, and threat actor activity at scale.
Experience in responsible AI and Safety-by-Design.
Experience handling user data and privacy.
Solid understanding of machine learning algorithms (supervised and unsupervised learning, anomaly detection, etc.) and practical implementation.

Technologies

Large language models (LLMs)
Azure AI Foundry
Tool-use loops
LLM-as-judge evaluation
AI coding assistants
Machine learning
Precision/recall tradeoffs

What We Value

Collaboration
Empathy
Quality
Positive Impact
Shipping

Compensation

The base salary range for this role is USD $107,700.00 to USD $285,900.00 per year.

Locations

Remote (United States)

Leadership Principles

GitHub values: Customer-obsessed, Ship to learn, Growth mindset, Own the outcome, Better together, Diverse and inclusive
Manager fundamentals: Model, Coach, Care
Leadership principles: Create clarity, Generate energy, Deliver success

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1mo ago

Secure AI Engineer Manager

Accenture Scottsdale, AZ

Scottsdale, AZ

1mo ago Closed

$87k - $294k/yr Full time Manager Agentic Ai Ai Enabled Security

This position is no longer accepting applications (closed Aug 26, 2026).

Job Description

Accenture seeks a highly skilled Secure AI Engineer Manager to lead delivery of secure AI client workstreams, build security tooling, and advance practice assets with a focus on Security for AI and AI for Security across LLM platforms while mentoring teams.

Responsibilities

Deliver cybersecurity focused Secure AI solutions that accelerate enterprise AI adoption and safeguard AI enabled operations
Design, configure, and validate prototype and production secure AI deployment solutions, ensuring end-to-end integration
Collaborate with project teams, team leaders, project delivery leads, and client stakeholders to develop standout AI Security and Governance offerings built on LLM platforms, frontier‑grade models, agentic frameworks, and AI/MCP gateways including Anthropic Claude, OpenAI, and Azure OpenAI
Build trusted relationships with clients and key advisory stakeholders
Articulate the business case for the recommended secure AI solution
Support Accenture sales efforts as needed
Pursue ongoing learning to strengthen foundational AI, AI security, emerging technology, and business expertise
Travel may be required; frequency varies from 0 to 100 percent based on business needs and client requirements

Requirements

Minimum 5 years of total experience in Cybersecurity with depth in at least one area such as AppSec, SecOps/detection engineering, IAM, cloud security, offensive security/penetration testing, GRC, or responsible AI
Minimum 1 year of hands-on proficiency with agentic coding tools: Claude Code, Cursor, GitHub Copilot, or Codex, with daily use
Minimum 1 year of experience with AI architecture fundamentals: LLMs, agentic systems, A2A, RAG, MLOps pipelines, MCP, AI Gateway, and model serving
Minimum 1 year of experience in AI specific security: OWASP LLM Top 10, prompt injection, adversarial inputs, AI supply chain risks
Minimum 1 year of experience in threat modeling for AI systems (STRIDE, PASTA, or equivalent) applied to LLM deployments and agentic pipelines
Cloud platform security fundamentals certification (AWS, Azure, or GCP)
Bachelor's degree or equivalent (minimum 12 years) of work experience. If Associate’s Degree, at least 6 years of work experience

Technologies

Claude Code
Cursor
GitHub Copilot
Codex
Anthropic Claude
OpenAI
Azure OpenAI
AI Gateway
MCP
AWS
Azure
GCP
LLMs

Benefits

Medical, dental, vision, life, and long-term disability coverage
401(k) plan
Bonus opportunities
Paid holidays
Paid time off

REQUESTING AN ACCOMMODATION

Accenture is committed to equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation during the recruiting process and employment. If you are hired and require accommodation to perform essential functions, you will participate in our reasonable accommodation process. Accommodations provided during recruiting do not guarantee future accommodations once hired.

If you would like to be considered for opportunities with Accenture and have accommodation needs such as for a disability or religious observance, please call toll free at 1 (877) 889-9009 or contact us via email or talk with your recruiter.

Equal Employment Opportunity Statement

We believe no one should be discriminated against because of protected characteristics. All employment decisions are made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis protected by applicable law. Our diverse workforce drives innovation, competitiveness, and creativity.

Other Employment Statements

Applicants for employment in the US must have work authorization that does not require visa sponsorship now or in the future
Candidates currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process; a criminal conviction history is not an absolute barrier to employment

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Llm Security Data Jobs

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