Principal AI Engineer (Autonomous Agent) Job at PointClickCare (Mississauga)

Distinguished Engineer- AI Agentics Engineering

At CVS Health, we’re building a world of health around every consumer and surrou...

Location

United States , Woonsocket

Salary:

175100.00 - 334750.00 USD / Year

CVS Health

Expiration Date

March 31, 2026

Requirements

15+ years of Software Engineering experience required
7+ years in AI/ML engineering with 3+ years specifically in agentic AI or autonomous systems
Proven experience building multi-agent systems from scratch (not just fine-tuning existing models)
Deep expertise in: Multi-agent system architectures: Actor model frameworks, distributed consensus protocols, agent communication standards (FIPA-ACL, KQML, MCP, A2A), and coordination patterns (hierarchical, peer-to-peer, marketplace-based)
LLM Integration Platforms: OpenAI API, Anthropic Claude API, Azure OpenAI Service, Google Vertex AI, and on-premises LLM deployment (vLLM, TensorRT-LLM, Ollama)
Agentic Frameworks: LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and custom agent runtime environments
Tool-using AI Systems: Function calling implementations, API integration patterns, IDE (Cursor, Windsurf), Notebooks (Jupyter), tool selection algorithms, and sandbox execution environments for safe tool usage
Agent Orchestration Platforms: Kubernetes-based agent deployment, Apache Airflow for agent workflows, Temporal for durable agent executions, Agentspace, and event-driven architectures (Apache Kafka, RabbitMQ)
Vector Databases & Knowledge Systems: Pinecone, Weaviate, Chroma, Qdrant for agent memory systems, and knowledge graph technologies (Neo4j, Amazon Neptune, Apache Jena)
Real-time Inference Infrastructure: NVIDIA Triton Inference Server, Ray Serve, TorchServe, and streaming architectures for sub-100ms agent response times

Job Responsibility

Strategic Agentic Architecture & Design: Drive the end-to-end architecture for highly scalable, multi-agent systems that can operate autonomously across complex enterprise workflows
Partner with other Principal Engineers, AI Architects, and executive leadership to shape the long-term agentic roadmap
Champion best practices for agent reliability, interpretability, safety, and performance optimization
Agent Platform Development & Orchestration: Oversee the design and development of new AI agent platforms from the ground up
Implement robust agent lifecycle management, including spawning, monitoring, termination, and inter-agent communication protocols
Foster an engineering culture that values agent autonomy, emergent intelligence, and continuous learning capabilities
Multi-Agent Systems & Emerging AI Technologies: Provide thought leadership on how multi-agent systems, large language models, and reinforcement learning create unique demands on infrastructure
Understand how to move AI agents from proof-of-concept to production-ready autonomous systems
Evaluate and recommend emerging agentic technologies and guide their integration into the broader technology stack
Cross-Functional Leadership & AI Mentoring: Serve as a key technical advisor for C-level executives and product leaders

What we offer

Affordable medical plan options
401(k) plan (including matching company contributions)
Employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching
Paid time off
Flexible work schedules
Family leave
Dependent care resources
Colleague assistance programs
Tuition assistance

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

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