This page tracks remote ai engineer openings that are location-eligible for Texas.
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• Define technical strategy across multiple AI initiatives, driving architectural decisions, influencing product and research direction, and aligning engineering investments across teams to maximize long-term business and clinical impact. • Design, build, train, evaluate and improve advanced machine learning and LLM-based systems for patient and provider-facing products (e.g., conversational AI, personalization, user understanding, clinical decision support, chronic care management). • Own problems end-to-end: scope the problem with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with the right monitoring and guardrails. • Develop robust evaluation frameworks — offline benchmarks, human-in-the-loop review, online experiments — that give us confidence our models are safe, accurate, and improving over time. • Build and improve the platform that lets the team move quickly: data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers. • Partner closely with clinicians, product, and engineering to translate medical and operational requirements into ML problems and ship measurable improvements to patient and clinician experience. • Set technical direction for your area, mentor other engineers, and raise the bar on engineering and scientific rigor. The scope of leadership scales with seniority. • Stay close to the literature and the rapidly evolving AI ecosystem; bring back what is most useful for our patients and our team.
• Lead the technical execution of complex AI initiatives, owning the design and delivery of solutions within a product or technical domain while partnering with senior engineers on broader architectural direction. • Design, build, train, evaluate and improve advanced machine learning and LLM-based systems for patient and provider-facing products (e.g., conversational AI, personalization, user understanding, clinical decision support, chronic care management). • Own problems end-to-end: scope the problem with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with the right monitoring and guardrails. • Develop robust evaluation frameworks — offline benchmarks, human-in-the-loop review, online experiments — that give us confidence our models are safe, accurate, and improving over time. • Build and improve the platform that lets the team move quickly: data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers. • Partner closely with clinicians, product, and engineering to translate medical and operational requirements into ML problems and ship measurable improvements to patient and clinician experience. • Set technical direction for your area, mentor other engineers, and raise the bar on engineering and scientific rigor. The scope of leadership scales with seniority. • Stay close to the literature and the rapidly evolving AI ecosystem; bring back what is most useful for our patients and our team.
Build invincible apps.
• Work as a software engineer • Maintain and expand a deep understanding of agentic coding • Design and build agentic coding systems that we can trust to deliver high-quality outputs • Develop a deep understanding of AI application development patterns and techniques, including emerging approaches and architectures. • Take end-to-end ownership of new features, working with other teams to deliver exceptional reliability and a great developer experience. • Work with multiple programming languages: Python and TypeScript, Java, Go. • Serve as a domain expert on AI design patterns, collaborating with field staff to provide best-practices and canonical examples. • Work directly with our developer community to debug issues that need expert attention and get feedback on Temporal features and APIs. • Write public technical documentation describing Temporal concepts and APIs. • Go the extra mile to support a customer in need, on the rare occasion that our teams’ engineering expertise is needed. • Travel to meet your coworkers for a week once or twice a year. • Attend the occasional developer conference to talk about how great Temporal is (optional).
Do it all with Luxury Presence. Build your brand, expand your network, & close more deals.
Luxury Presence is building the AI growth platform for real estate. Backed by Bessemer Venture Partners and other top investors, we're a Series C company that has hit $100M in annual recurring revenue. More than 90,000 real estate professionals, including over 30% of the WSJ Real Trends top 100 agents in the United States, use us to run and grow their business. The OpportunityWe don't just use AI. We build with it, ship with it, and think with it. We're in the top 1% of companies applying AI effectively, not just to our products, but to how we build them. With an unlimited budget for Anthropic tokens, our engineers use AI agents to write, review, and ship production code every day. We're building toward a world where humans design systems and AI builds them, and we're already further along that path than almost anyone else. As a Staff Software Engineer, you'll be a technical leader at the center of this transformation. You'll shape platform architecture, drive AI-powered product delivery, and raise the bar for what a small, AI-augmented engineering team can accomplish. This is a role for someone who already lives in their terminal with AI, who has strong opinions about how AI changes system design, and who wants to help define what a next-generation engineering organization looks like. What You'll DoDrive large-scale technical initiatives. You'll take complex, cross-functional projects from concept through production, aligning architecture decisions with business goals and shipping outcomes that matter. Ship AI-native product experiences. Working closely with product, design, and AI teams, you'll deliver intelligent features that leverage LLMs, agent frameworks, and real-time data to transform how real estate professionals run their businesses. Lead system design in an AI-native codebase. You'll own the architecture of critical platform capabilities, from our AI-powered site builder pipeline to our multi-tenant infrastructure serving thousands of real estate businesses. You'll set patterns that other engineers follow. Define how we build, not just what we build. You'll shape our engineering standards, review practices, and developer tooling. You'll have a direct hand in evolving how AI agents integrate into our development workflow. Mentor and elevate engineers across the org. Staff Engineers at LP are force multipliers. You'll raise the technical bar across teams, coach engineers through hard design problems, and influence career growth. What We're Looking ForAttributes - You already build with AI daily. You use Claude Code as a core part of your workflow, not as a novelty - You have strong opinions, loosely held, about how AI changes software architecture, team structure, and engineering culture - You think in systems. You connect technical decisions to customer outcomes and long-term business value - You communicate clearly and directly. You can explain complex tradeoffs to product, design, and executive stakeholders - You're energized by ambiguity and speed. You thrive in a fast-growing company where the roadmap evolves and ownership is real - You like to have fun at work. We take our craft seriously, but we don't take ourselves too seriously. We celebrate wins, crack jokes, and genuinely enjoy building together Skills and Experience - 8+ years of professional software engineering experience, with meaningful time in senior or staff-level roles - Deep expertise in TypeScript, Node.js, and React - Experience designing and operating scalable microservice architectures in cloud-native environments (AWS preferred) - Strong understanding of GraphQL, event-driven systems (Kafka, SQS), and distributed databases (PostgreSQL, DynamoDB, Elasticsearch) - Proven track record leading high-impact initiatives from concept through production in a SaaS environment - Expert-level grasp of software design principles and experience with multi-tenant platform architectures Tech Stack - Frontend: React, Tailwind, Apollo - Backend: Node/TypeScript Microservices - Data: Postgres, Redis, Elasticsearch - Infrastructure: AWS, Kubernetes, Lambda, Temporal - Messaging: Kafka, SQS Join us in shaping the future of real estate The real estate industry is in the midst of a seismic shift, and the future belongs to those who break new ground. As one of the fastest-growing companies in the proptech and marketing sectors, Luxury Presence challenges the status quo of what technology can do for real estate agents, leaders, and brokerages. We're a team of agile and tenacious innovators working collaboratively to drive the industry forward. Together, we build game-changing products that empower modern real estate entrepreneurs to dominate their markets. From award-winning web design to agile SEO solutions to cutting-edge AI tools, we deliver tech that anticipates market shifts and keeps our clients ahead of their competition. Founded in 2016 by Stanford Business School alum Malte Kramer, Luxury Presence has grown to a global team ranked on the Inc. 5000 fastest-growing companies list three years in a row. We're backed by world-class investors, including Bessemer Venture Partners, NextEquity Partners, Toba Capital, and Switch Ventures, and have raised $89 million to date. More than 18,000 real estate businesses rely on our platform, including 30% of the Wall Street Journal RealTrends top agents and teams. Additionally, many of the industry's most powerful brokerages rely on Luxury Presence as a trusted business partner. Every year since 2020, Luxury Presence has ranked on BuiltIn's Best Place to Work lists. HousingWire named our founder and CEO a 2024 Tech Trendsetter, we've received several Tech100 Awards, and we just scored an Inman Innovation Award for Best AI-Powered Platform. Luxury Presence is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
We transform workforces today to power the data economy of tomorrow. | #6 on LinkedIn's Top Startups 2022 list
• Deliver engaging, effective live sessions (virtual, via Microsoft Teams) covering AI-augmented full-stack development: agentic workflows, spec-driven development, Claude Code, GitHub Copilot, governance and compliance in AI-assisted engineering • Adapt delivery based on both evolving content (the underlying engineering platform is being built in parallel) and learner needs — reading the room to calibrate depth for beginners vs. more advanced participants • Review pre-work to understand where the cohort is struggling, then focus live time on the hard parts • Collaborate with SMEs and curriculum designers to stay current on what's being taught and why
• Architect and build production systems across a multi language stack: C#/.NET services, Python AI and data pipelines, and occasional TypeScript • Set the example for an AI forward, high technical standard across the broader engineering organization, leading through craft rather than organization wide authority • Design and drive adoption of offline evaluation frameworks (test suites, golden datasets, regression harnesses wired into CI/CD) for LLM based and other non deterministic components • Build online evaluation and monitoring that continuously assesses live model and system behavior in production, including drift and regression detection • Partner with engineering leadership to surface systemic risks in AI features, such as reliability, correctness, and drift, and drive the fixes • Lead architecture reviews for major initiatives and mentor senior and staff engineers on system design, evaluation methodology, and AI forward practices • Prototype and ship new AI capabilities
We’re the technology workforce development company that helps individuals and organizations transform with tech skills.
• Serve as the owner of Pluralsight’s expert point of view which forms the foundation of these offerings. • Design solution products to scope the offering, its audience, problem it addresses, business outcome it enables, structure, and milestones. • Identify frameworks, messaging, courses, hands-on labs, and program management needed to deliver successful customer outcomes. • Maintain and communicate a 12–18 month roadmap related to your solutions, including new levels, variants, and accelerators tied to market shifts in AI. • Systematically test and iterate solution design using experiments and data. • Be responsible for solution‑level benchmarks including pipeline, win rate, adoption, and cohort completion / outcome metrics. • Partner with Sales on opportunity strategy, referenceable customer logos, and driven plays. • Continuously monitor and interpret changes in technical expertise. • Identify, engage, and work with SMEs, translating complex technical knowledge into accessible, high-quality learning experiences. • Represent your solutions area with executive presence and credibility. • Actively engage internal collaborators, enterprise customers, SMEs, and industry audiences to build trust and drive alignment.
Come join the movement....we are a vehicle to healthy living!
Role Description The Sr. Software Engineer II - AI will lead the build of GenAI-powered product experiences and the shared AI platform infrastructure that powers them. This includes: - RAG pipelines over the iHerb catalog and customer reviews - LLM-driven personalization - A conversational Wellness Agent - Agentic workflow systems - The evals and MLOps layer that makes AI features production-grade and repeatable Specializations within this track include: - RAG and personalization - Agent framework and tool use - Evals and guardrails - LLM application development for internal business functions such as marketing automation and BI agents Qualifications - AI-driven SDLC: hands-on experience shipping production code with AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor - Full-stack awareness: comfortable contributing across layers of the stack - Production ownership: experience owning features end-to-end from spec through deployment - Code quality fundamentals: strong grasp of software design principles, automated testing, code review, and CI/CD - Fully autonomous; drives technical decisions within the team; mentors junior engineers - Python proficiency; comfortable building and operating production LLM applications - Hands-on experience with at least one specialization: RAG and retrieval systems, LLM evaluation, agentic frameworks, or LLM-based workflow automation - Understanding of prompt engineering, context window management, and LLM output quality tradeoffs - Familiarity with vector databases, embedding models, or semantic search - High degree of accuracy and attention to detail - Excellent organization skills and ability to multi-task Requirements - Generally requires a minimum of 10+ years of software engineering experience - Bachelor’s Degree in Computer Science or related field preferred, or a combination of education and equivalent work experience Benefits - The expected salary range for this role is $187,000.00 - $235,000.00 USD - The actual base pay offered will be determined by factors such as the candidate's relevant experience, education, geographic location, and internal equity Physical Demands The physical demands described here are representative of those that must be met by a Team Member to successfully perform the essential functions of this job: - Regularly required to talk and hear - Frequently required to sit, walk, climb stairs, use hands and fingers, bend, stoop and reach with hands and arms - Occasionally lift or move office products and supplies up to 25 pounds Work Environment - The noise in the work environment is usually moderate - Hectic, fast-paced with multi-level distractions - Professional, yet casual work environment - Office / Warehouse environment - Ability to work extended hours as required
• Design, build, and scale production-ready Multi-Agent Systems (MAS) and complex AI workflows. • Bridge the gap between simple LLM prompting and robust, deterministic, enterprise-scale software engineering. • Leverage ADK to orchestrate specialized micro-agents, build reliable graph-based workflows, and integrate AI agents with enterprise datastores, APIs, and Model Context Protocol (MCP) tools. • Move AI from conceptual prototypes to high-throughput, mission-critical business systems deployed on Agent Engine.
• Own the enterprise identity platform as an engineering system — architect SSO integrations, lifecycle workflows, MFA policy, and group provisioning in Okta using IaC as the source of truth; configuration drift is a bug, not a ticket • Engineer the identity lifecycle management layer — design access control models and codify provisioning/deprovisioning workflows in IaC, partnering with HR systems to eliminate manual access operations and return clean provisioning capability to the helpdesk tier • Engineer access governance across the cloud and SaaS portfolio — own role assignments, group structures, and access controls across cloud infrastructure and collaboration platforms; design and automate periodic access reviews so auditability is structural, not procedural • Harden the device-to-identity trust boundary — own device trust integrations between our identity provider and MDM platforms, ensuring device compliance signals are correctly evaluated in access policy and that the control surface is fully codified • Rationalize and consolidate legacy identity surface — lead the technical cleanup of orphaned accounts, stale SSO integrations, and guest access sprawl across the SaaS portfolio; treat this as technical debt reduction with measurable outcomes • Build the IAM measurement layer — define, instrument, and track KPIs (access review completion rates, provisioning latency, orphaned account age, ticket volume trends) that justify investment decisions and demonstrate program maturity to Security leadership • Define the identity layer of our access request platform — architect the entitlement structures and access controls exposed through our self-service access tooling; codify the configuration in IaC and own the integration contract between identity infrastructure and the employee-facing access experience • Contribute to a unified service catalog — ensure identity workflows are clearly surfaced through a single employee-facing entry point and that the handoff between self-service and engineer-owned provisioning is unambiguous • Use AI coding agents as a first-class part of the identity engineering workflow — draft and validate Terraform modules, provisioning logic, and access-policy changes with AI assistance, and own review of anything AI-generated before it reaches production identity infrastructure
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Python, TypeScript, Go, Cloud, Java, .NET
