Role Description Life360 is hiring an AI-Native Engineer — a senior full-stack engineer who doesn’t just use AI tools, but thinks natively in them. You’ll be central to how the Circle Expansion team builds product, where AI has reshaped how the entire team designs, builds, and ships. - Design and build features that serve some of our most important and fastest-growing member segments: aging parents, pre-teens with wearables, sports teams, and school communities. - Build and evolve our modern AI-Native engineering workflows — from how we write code to how we run standups and think about team velocity. Qualifications - 7+ years of experience building high-quality, consumer-scale software products. - At least 1 year of hands-on experience prompting, evaluating, and building with LLMs. - Strong proficiency in mobile development (iOS or Android). - Deep experience with agentic workflows, prompt engineering, context window management, and MCP/function calling. - A track record of using AI tooling to multiply your own output. - Strong communication and collaboration skills. - A genuine excitement for defining what it means to be AI-Native. - Empathy for the humans behind the product. - Bachelor’s Degree in a Technical field, or equivalent experience. Requirements - Mobile experience is strongly preferred (iOS or Android). - Exceptional full-stack or backend engineers are also encouraged to apply. Benefits - Competitive pay and benefits. - Medical, dental, vision, life and disability insurance plans (US and Canada). - 401(k) plan with company matching (US) / RRSP with DPSP matching (Canada). - Employee Assistance Program (EAP) for mental well-being. - Flexible PTO, plus several company-wide days off throughout the year. - Winter and Summer week-long synchronized company shutdowns. - Learning & Development programs. - Equipment, tools, and reimbursement support for a productive remote environment. - Free Life360 Platinum Membership for your preferred circle. - Free Tile Products.

Role Description We at Coforge are hiring a Senior Developer - AI Engineer with the following skill set. - Develop and maintain high-performance microservices using Python and FastAPI. - Support the migration of frontend components from Angular to React and backend services from .NET/Node. - Build and integrate RAG-based LLM features and Vector Databases into industrial engineering workflows. - Collaborate with Data Engineers to ensure application logic aligns with Databricks and Microsoft Fabric architectures. - Implement automated tests and documentation for new AI service components to ensure production readiness. Qualifications - Experience with Python: Specifically FastAPI for building microservices and APIs. - Frontend Development: Professional experience with ReactJS (TS/JS). - Backend Versatility: Experience with .NET/C# or Node.js. - AI/LLM Implementation: Experience implementing RAG patterns and working with Vector Databases (e.g., ChromaDB). Requirements - Migration Experience: Familiarity with transitioning applications from Angular to React. - Database Knowledge: Experience with MongoDB and relational databases. - Cloud Services: Experience with Azure ecosystem and Azure AI Services. - Data Platforms: Familiarity with Databricks or Microsoft Fabric. - Authentication: Experience with Azure AI/Entra ID (formerly Cognito/AD). - Domain Knowledge: Interest in hydraulics or industrial engineering calculations. - Testing: Experience with unit and integration testing for AI-driven applications. Company Description At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Role Description Precisely is hiring a Director of AI Engineering to lead the design, development, and deployment of internal enterprise AI solutions that drive business transformation and operational efficiency. This is a hands-on technical leadership role responsible for building AI systems, setting engineering standards, and leading a team of AI engineers. The role spans the Microsoft Copilot Studio, Azure AI Foundry, and Claude Enterprise ecosystems, delivering AI-based employee experiences, and automating and augmenting workflows that reduce cost, accelerate cycle times, and enable revenue. - Design and operationalize agentic AI systems with multi-step workflows, orchestration frameworks, and human-in-the-loop patterns. - Architect and build AI systems including agentic workflows, RAG pipelines, evaluation harnesses, orchestration layers, and prompt engineering. - Prototype new AI patterns and capabilities to stay ahead of the rapidly evolving landscape. - Set technical standards through code reviews, design documentation, and reference implementations. - Hire, mentor, and develop an agile team of AI engineers. - Represent AI engineering in executive discussions, vendor partnerships (Microsoft, Anthropic), and cross-functional planning. - Define data requirements for AI models and validate pipeline quality, governance, and freshness. - Coordinate with Enterprise Applications to integrate AI capabilities into existing business systems (Salesforce, NetSuite, Workato) without creating parallel systems or integration debt. - Prioritize AI use cases that enhance enterprise workflows through intelligent automation, predictive insights, and embedded copilot experiences. - Align on shared data models, integration patterns, and change management processes. Qualifications - 10+ years in software engineering with current, deep technical fluency and active production coding. - 2+ years leading or mentoring engineering teams (formal management or tech-lead experience). - Daily use of AI-assisted developer tools (GitHub Copilot, Claude Code, Cursor, or equivalent). - Strong architecture skills in cloud-native AI on Microsoft Azure (Azure AI Services, Azure OpenAI, Entra ID, Microsoft Graph). - Demonstrated ability to co-architect across platform, data, and enterprise application teams. - Track record of translating ambiguous business problems into shipped AI solutions. - Experience establishing AI governance, evaluation, and quality frameworks. - Ability to communicate complex technical concepts to executive and non-technical audiences. Preferred Skills - Background in data integration, data quality, or master data management. - Experience with enterprise application ecosystems (Salesforce, NetSuite, Workato, ServiceNow). - Knowledge of AI regulatory frameworks (NIST AI RMF, EU AI Act, ISO 42001). Benefits - This position is 100% remote anywhere in the US.

• Define and own end-to-end technical architecture for a dual-mode agentic AI system across offline (edge) and cloud-connected (AWS Bedrock) environments • Drive architectural decision-making across agentic orchestration, data synchronization, voice and chat interfaces, and cloud infrastructure; author and maintain Architecture Decision Records (ADRs) • Act as the primary technical authority within the Engineering POD and the key technical interface with client stakeholders • Bring an AI-forward development practice to every phase of the engagement — using tools like Claude, Cursor, and agentic coding assistants as force multipliers across implementation, code review, and technical documentation • Guide and align the engineering team across AI/ML, full stack, and integration workstreams • Take direct implementation ownership across cloud infrastructure provisioning, local SQLite data layer, cloud data mirror, STT/TTS pipeline integration, and REST API surface • Build and configure the AWS environment end-to-end — including Bedrock, Guardrails, storage, and connectivity services • Implement the edge-to-cloud data synchronization strategy between offline local storage and AWS-hosted data stores • Contribute to agentic orchestration implementation, integration testing, and iterative deployment; support incoming team members with onboarding and context transfer • Design the agentic orchestration layer with tool-use, contextual memory, and conversational interaction patterns for both offline and connected modes • Select an edge LLM based on prior experience with comparable hardware profiles; configure AWS Bedrock with Guardrails for connected-mode reasoning and content safety • Collaborate with the AI/ML Engineer on prompt engineering, model evaluation, and proactive recommendation logic • Ensure architectural consistency and integration quality across voice (STT/TTS) and chat modalities on a shared backend • Provide technical quality assurance and architectural governance across all POD workstreams • Lead cross-functional engineering coordination across AI/ML, full stack, product, and UX tracks • Drive iterative delivery cadence — shipping testable software at each phase review checkpoint and supporting investor-facing demonstrations and POC readouts • Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace.