Principal AI Engineer (Autonomous Agent) Job at PointClickCare

Principal AI Engineer (Autonomous Agent)

Location

United States

Salary:

Not provided

PointClickCare

Expiration Date

Until further notice

Requirements

Have you built or worked with LLM-based autonomous agents before? Can you briefly describe one example?
Which agent or LLM frameworks have you used? (Examples: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI)
Would you consider yourself an expert-level Python engineer? Can you share examples of complex systems you’ve built with Python?
Have you implemented authentication, access control, or security mechanisms for AI/ML systems or agent workflows?
Have you integrated AI agents with external systems or APIs (e.g., tools, data sources, internal apps)?

Fulltime

Principal AI Engineer (Autonomous Agent)

Location

Canada , Mississauga

Salary:

Not provided

PointClickCare

Expiration Date

Until further notice

Requirements

Have you built or worked with LLM-based autonomous agents before?
Which agent or LLM frameworks have you used? (Examples: LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI)
Would you consider yourself an expert-level Python engineer?
Have you implemented authentication, access control, or security mechanisms for AI/ML systems or agent workflows?
Have you integrated AI agents with external systems or APIs (e.g., tools, data sources, internal apps)?
Are you legally authorized to work in Canada for our company?

Fulltime

Principal AI Engineer (Autonomous Agent)

The AI Engineer – Autonomous Agent will work closely with the Product and Engine...

Location

Canada , Mississauga

Salary:

169000.00 - 188000.00 CAD / Year

PointClickCare

Expiration Date

Until further notice

Requirements

Expert level in Python, frameworks, and functional programming principles
Experience designing and implementing LLM agent workflows, and familiarity with frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, and AutoGen.

Job Responsibility

Collaborate with product and engineering teams to translate product objectives into autonomous agent-based solutions
Design and build new agent data types, and pipelines that enable agents frameworks, and workflows to coordinate reasoning, function calling, actions
Develop and optimize autonomous agents leveraging LLMs, planning algorithms, and multi-step reasoning approaches
Implement comprehensive security mechanisms for autonomous agents, including authentication, role-based access control, audit logging, and compliance monitoring
Integrate agents securely with existing systems, APIs, and data sources with secure communication protocols

What we offer

Benefits starting from Day 1!
Retirement Plan Matching
Flexible Paid Time Off
Wellness Support Programs and Resources
Parental & Caregiver Leaves
Fertility & Adoption Support
Continuous Development Support Program
Employee Assistance Program
Allyship and Inclusion Communities
Employee Recognition … and more!

Fulltime

Machine Learning Engineer - AI Assistant + Autonomous AI Agents

Glean is looking for senior engineers who will provide expert-level individual c...

Location

United States , San Francisco Bay Area

Salary:

240000.00 - 300000.00 USD / Year

Glean

Expiration Date

Until further notice

Requirements

2+ years as a Staff Engineer, Principal Engineer, or equivalent
5+ years of industry experience in AI or Machine Learning Engineering
Experience working with agentic frameworks, reinforcement learning, natural language processing, or other large systems involving machine learning
Proven ability to design, build, and ship production-ready systems
Proficiency in your ML framework of choice
Strong coding skills (Python, Go, Java, C++, ...)
Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company
A proactive and positive attitude to lead, learn, troubleshoot, and take ownership of both small tasks and large features

Job Responsibility

Build frameworks for LLM-powered agents to use tools and knowledge sources effectively
Invent new agentic architectures and signals to improve reasoning, planning, and personalization in workplace AI assistants
Design and optimize reinforcement learning and fine-tuning approaches to improve the quality of agentic systems
Lead development of scalable evaluation, benchmarking, and optimization loops for agents in production
Drive technical strategy and mentor other engineers, raising the technical bar across the team
Write robust, maintainable, and well-tested code that powers enterprise-grade assistants and agents

What we offer

Medical, Vision, and Dental coverage
generous time-off policy
opportunity to contribute to your 401k plan
home office improvement stipend
annual education and wellness stipends
regular events
healthy lunches daily

Fulltime

Principal Ai Engineer (Prisma Browser - Agents Platform)

The Prisma Browser group is building an agentic development lifecycle, an infras...

Location

Israel , Tel Aviv

Salary:

Not provided

Palo Alto Networks

Expiration Date

Until further notice

Requirements

At least 8+ years of experience in software development, architecture, or owning operational systems in production
Computer Science B.Sc. or equivalent education or equivalent military experience required
A product builder's mindset: you can extract requirements, talk to stakeholders, and tell the difference between what's important and what's noise
Experience in building production grade agents. Deep understanding of the agent loop, its states and transitions. You know how to build it correctly, not just use it
Positive 'can-do' mindset, able to work independently and within a team
Hands-on experience with LLM APIs, including a practical, highly-skeptical understanding of token costs, caching, context windows, and model failure points
You know how to build the right context for a task, including memory systems, session storage, and vector databases
You understand where LLMs fail and how to design around those failure points
You've used traces or observability tooling to diagnose and improve agent behavior
A systems-level background that touches reliability, observability, or platform engineering, with a strong preference for writing narrow, deterministic code over building hypothetical abstractions

Job Responsibility

Design and implement automated evaluation loops, static analysis, and rigorous quality gates to ensure the ADLC process doesn't just write code, but consistently produces great, production-ready code
Help the team tackle complex, hard problems to elevate our autonomous development product from 'good' to 'excellent'
Lead complex initiatives in Context Engineering and Prompt Engineering
Manage and orchestrate the complex ecosystem of autonomous agents utilized for internal development
Serve as a leading individual in a very strong team professionally and personally
Find space for growth to push the entire team or group forward
View prompt engineering as a core engineering discipline—where rewriting agent behavior is a versioned, reviewed, and tested code change
Act with a debugging temperament
conduct deep-dive analyses of raw agent transcripts to diagnose non-deterministic failures and ascertain root causes instead of merely working around them

Fulltime

Principal AI Engineer

Location

Canada , Mississauga

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Experience: Extensive experience in designing and building AI/ML solutions, with a significant focus on generative AI and Large Language Models (LLMs)
Gen AI Expertise: Deep understanding of modern AI architectures and techniques, including Retrieval-Augmented Generation (RAG), fine-tuning, function calling, and AI agentic workflows
Programming Proficiency: Expert-level skills in Python and extensive experience with core AI/ML libraries such as PyTorch, TensorFlow
System Design: Proven ability to architect and develop large-scale, distributed, multi-tier applications. Strong knowledge of microservices, API design, and system integration
MLOps: Solid understanding of MLOps principles and experience with tools for model versioning, deployment, monitoring, and lifecycle management
Leadership: Demonstrated experience serving as a technical lead, architect, or principal engineer, with a track record of mentoring team members and driving projects to completion

Job Responsibility

Architectural Leadership: Design and architect end-to-end generative AI solutions, from proof-of-concept to production, ensuring scalability, performance, and reliability
Technical Strategy: Develop and maintain a comprehensive strategic roadmap for generative AI adoption, evaluating new models, techniques, and platforms to keep our capabilities at the forefront of the industry
Solution Development: Lead the hands-on development of complex AI systems, including Retrieval-Augmented Generation (RAG) pipelines, autonomous AI agents, fine-tuning workflows, and custom model integrations
Best Practices & Standards: Establish and govern best practices for the full AI development lifecycle, including prompt engineering, model evaluation, MLOps, and data management
Cross-Functional Partnership: Collaborate closely with multiple management teams and business units to identify high-impact use cases and ensure the successful integration of AI solutions to meet business goals
Mentorship & Guidance: Serve as a senior advisor and coach to other engineers and analysts, fostering a culture of innovation and technical excellence. Allocate work and provide technical direction to the team
Risk & Compliance: Appropriately assess risk when business decisions are made, demonstrating consideration for the firm's reputation and safeguarding its clients and assets. Drive compliance with all applicable laws, rules, and regulations, particularly those related to AI ethics, data privacy, and model bias
Innovation and Research: Stay abreast of the latest advancements in generative AI research, and translate state-of-the-art developments into practical, innovative solutions

Fulltime

Principal Software Engineer, AI Developer Tools

At Docker, we make app development easier so developers can focus on what matter...

Location

United States , Seattle

Salary:

232000.00 - 319000.00 USD / Year

Docker

Expiration Date

Until further notice

Requirements

10+ years software engineering experience with 3+ years in Staff or Principal Engineer roles
Deep expertise in AI/ML technologies with hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools
Strong understanding of LLM APIs (OpenAI, Anthropic, etc.), prompt engineering, agent orchestration frameworks, and practical applications of AI in software development workflows
Proven track record of architecting and building highly scalable distributed systems and developer-facing platforms
Production experience with modern cloud-native infrastructure including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines
Proficiency in Go (preferred), Rust, Java, or Python with strong software engineering fundamentals
Experience designing developer tools, platform engineering systems, or internal tools that enable other teams
Exceptional product and platform mindset considering business outcomes, developer experience, and technical trade-offs
Strong communication skills with ability to influence technical and non-technical stakeholders across the organization
Track record of technical mentorship and elevating engineering teams' capabilities

Job Responsibility

Define the long-term technical vision and architecture for AI-powered developer tools and the self-service platform that enables teams to build their own AI agents
Establish architectural patterns, technical standards, and best practices for LLM integration, AI agent development, and production AI systems serving developers
Lead technical strategy for platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools
Design highly available, scalable infrastructure for hosting AI agents and developer tools with predictable performance and intelligent resource management
Drive technical decisions on AI technology choices, LLM provider strategies, prompt engineering approaches, and agent orchestration frameworks
Partner with Senior Manager and product leadership to align technical architecture with business objectives and productization opportunities
Architect and build production-ready AI agents for developer productivity including code review assistants, test generators, deployment diagnostics, and incident response automation
Design and implement the self-service platform infrastructure that reduces time-to-production for new AI tools from weeks to days
Build systems that accelerate adoption of AI-native development tools (Claude Code, Cursor, Warp) across Docker's engineering organization
Establish reliability, security, and performance standards for AI systems including SLOs, monitoring, incident response, and cost management

What we offer

Freedom & flexibility
fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup
we want you comfortable while you work
16 weeks of paid Parental leave
Technology stipend equivalent to $100 net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity

Fulltime

Principal Software Engineer - Agentix AI (Cortex XSIAM)

Your career: In this role, you will act as the primary architect of the "nervous...

Location

Israel , Tel Aviv

Salary:

Not provided

Palo Alto Networks

Expiration Date

Until further notice

Requirements

Keeps up with the latest research and stays on top of the fast-moving AI space, with a real passion for what’s happening in Generative AI
Regularly tries out different AI tools and sees how they’re useful in everyday work and life
Strong understanding of advanced prompting techniques like Chain-of-Thought, ReAct, and few-shot prompting
Experience working on model quantization or finding ways to optimize inference costs and token usage at scale
Hands-on experience with Python (FastAPI, Django, or Flask) or Go, with a solid grasp of async programming and microservices
Experience turning a vague product idea (e.g., "let's add a smart assistant") into clear, concrete technical requirements
Hands-on experience using frameworks like LangChain to build more complex LLM flows and agents
Experience working with vector databases
Comfortable building and using RESTful and GraphQL APIs, especially when dealing with low-latency streaming (WebSockets, Server-Sent Events)
Enjoys digging into "non-deterministic" systems - when an LLM fails, comfortable figuring out whether it’s the prompt, the retrieval, or the data

Job Responsibility

Act as the primary architect of the "nervous system" that bridges the gap between sophisticated AI models and real-world business logic
Design and maintain the critical infrastructure that enables intelligent, autonomous features to function reliably at scale
Take ownership of the entire data flow, where you will develop high-performance RAG (Retrieval-Augmented Generation) pipelines and complex agentic workflows
Champion system stability by implementing rigorous evaluation and monitoring frameworks

Fulltime

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Principal AI Engineer (Autonomous Agent)

Job Description

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Requirements

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