Beacon Biosignals is transforming precision medicine for the brain, from clinical development to clinical care. For Life Sciences partners, we offer the leading at-home EEG platform for clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our Diagnostics business is building the most comprehensive at-home platform for precision diagnostics, combining EEG and cardiopulmonary signals to deliver reimbursable assessments for sleep and central nervous system disorders. Together, we're changing the way patients are diagnosed and treated for any disorder that affects brain physiology. Beacon Biosignals is seeking a Staff Software Engineer to join our Datastore team. The Datastore sits at the heart of Beacon's platform. It defines our foundational data model and serves as the centralized repository and API for brain data collected from clinical studies, supporting the analytical tools, services, and applications used by our scientists, clinicians, and partners. This role emphasizes the design and scaling of backend systems for data infrastructure: PostgreSQL data models, Kafka-driven event pipelines, and the GraphQL API that makes scientific and clinical data usable - distinct from frontend development or end-user product surfaces. At this level you will lead the design of complex systems within the Datastore rather than individual components, own the pipelines that deliver dataset snapshots into our warehouse, and collaborate across platform, application and scientific teams to implement APIs that unlock new workflows in Beacon's expanding portfolio of clinical studies and digital health products. You should have experience writing complex SQL queries by hand, and should be prepared to reason about schema design, indexes, and query behavior as a matter of course. Two properties of our system that shape our work may influence your application. Our GraphQL API is generated from the PostgreSQL schema using PostGraphile, so a schema de
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About the Job: We are looking for a talented Senior Solutions Engineer at LaunchDarkly, you will be a trusted technical advisor to our largest and most important Enterprise prospects and customers. This role is a critical part of the Enterprise sales strategy at LaunchDarkly, serving as a trusted technical advisor to sales working to both land new customers and expand existing customers. The ideal candidate will have deep expertise in supporting multiple verticals. An ideal candidate is curious, excels in active listening, quickly and effectively builds custom demos and solutions, and demonstrates profound technical expertise with a customer-centric focus. Responsibilities: Drive technical discovery, architecture design, and PoC implementation throughout the pre-sales lifecycle. Partner with Account Executives and Customer Success Managers to craft compelling technical value propositions. Deliver high-impact demonstrations, workshops, and proposals tailored to C-level and technical stakeholders. Cultivate trust and credibility with customers, identifying technical champions and positioning as a strategic advisor. Liaise between customers and internal Product and Engineering teams to relay feedback and influence product roadmap. Lead cross-regional technical initiatives and enhance SE tools, processes, and frameworks for global scalability. Mentor junior team members, foster technical excellence, and share industry best practices across the SE team. Maintain expert-level knowledge of LaunchDarkly’s platform, integrations, industry trends, and emerging technologies. Respond to RFPs, and manage technical environments to support enterprise sales motions. Translate complex client requirements into scalable, sustainable, and technically sound solutions. Represent LaunchDarkly at industry events and customer engagements through travel as needed. Qualifications: 8+ years of experience in a solutions engineering, sales engineering, or systems architecture customer-faci
FEQ227R209 About the Role Databricks needs to understand what technical capability looks like across several large, fast-moving populations: employees, customers, and partners. Today that happens through role-based learning pathways and product-aligned enablement, an approach that can't keep pace with how quickly the platform, technology, and roles change. AI has also collapsed the half-life of technical proficiency, and for the first time, it makes a living, self-maintaining model of capability possible. In this builder role, you'll own systems for defining, measuring, and developing technical capability across Databricks learner audiences. You'll build a capability model that ties roles, skills, content, and credentials together and the instrumentation that shows where capability actually stands. What You'll Own Skills taxonomies, capability models, and learning context Define the skills taxonomies that make up technical capability and shape how they’re organized; what skills exist, which are adjacent, which are prerequisites, how quickly they go stale, and what sources are available to learners for developing and maintaining them. Observability and measurement Stand up instrumentation and AI-informed signals that show where capability stands and where it's drifting. Develop live signals, not a quarterly or monthly health index, to show how skills are moving and evolving. Anticipate where capability demand is heading. Product releases, market shifts, and role evolution are constant; track changes closely so emerging skills surface early and content and programs stay ahead of change. AI-native tooling Build the software that maintains the skills taxonomy and capability model, including LLM-driven skill extraction and organization, agentic pipelines that keep them current, automated drift and gap detection, and APIs that expose it all. Make the model reusable enterprise context that other systems, teams, and products build on vs. a training-only asset. Impact You'll
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Content-to-Discovery Platform team owns the end-to-end flywheel that turns raw content into the supply that our Pinners discover. As a Staff Product Manager on the team, you'll set direction across four connected pillars: acquisition of content and catalog data; processing, enrichment, and freshness; indexing for shopping and search; and retrieval and serving. You'll partner with engineering, data science, and product leaders across content, shopping, and search to acquire the right supply by category and domain, keep it fresh and accurate, index it with relevance built in, and serve it to the Pinner reliably, at scale, across markets. What you’ll do: Set and drive a multi-year strategy for the end-to-end content-to-discovery flywheel across acquisition, processing, indexing, and retrieval/serving. Own the roadmap for the infrastructu
About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Team This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Sales Engineers sit at the intersection of engineering, product, and go-to-market , shaping how LangChain is adopted in the field and feeding real-world insights back into the plat
About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Team This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market , shaping how LangChain is adopted in the field and feeding real-world insights back into the p
About The Weather Company: The Weather Company is the world’s leading weather provider, helping people and businesses make more informed decisions and take action in the face of weather. Together with advanced technology and AI, The Weather Company’s high-volume weather data, insights, advertising, and media solutions across the open web help people, businesses, and brands around the world prepare for and harness the power of weather in a scalable, privacy-forward way. The world’s most accurate forecaster globally, the company reaches hundreds of enterprise clients and more than 360 million monthly active users via its digital properties from The Weather Channel (weather.com) and Weather Underground (wunderground.com). AI is part of how we work: Human judgment, expertise, and creativity remain essential and are amplified by AI. We expect everyone in this role to use AI thoughtfully and proactively to accelerate their performance, improve the quality of their work, and explore new possibilities. We are looking for people who are curious, adaptable, and excited to help shape an AI-enabled culture that delivers better outcomes for our customers and our company. Job brief: We are seeking a Senior Project Manager to lead and drive key initiatives for our Enterprise business using Agile methodologies and AI tool integration. This individual will play a critical role in ensuring the successful delivery of complex projects, driving collaboration across cross-functional teams, and aligning project goals with strategic business objectives. The impact you'll make: Leading and Facilitating Agile Projects: Planning, coordinating, and managing Agile projects from initiation to completion. Facilitating Agile ceremonies (e.g., sprint planning, daily stand-ups, retrospectives) and promoting continuous improvement. Ensuring team adherence to Agile principles and practices. Project Scope and Delivery: Managing project scope, timelines, budgets, and resources. E
About Prodigal Prodigal is the connected AI platform leading financial institutions use to run their operations. We work with banks, lenders, credit unions, and other financial companies that lend money to people and manage those relationships over time. These institutions make millions of high-stakes decisions every day. Who should they reach? When should they reach them? What should they say or offer? When should a case move to a human? How should that change based on the borrower, the account, previous interactions, and the regulations involved? Getting those decisions right requires a deep understanding of the people, processes, rules, and edge cases behind them. Prodigal has spent the last eight years building that understanding. More than a billion interactions between financial institutions and their customers have shaped the intelligence, guardrails, and AI agents we now run in production across North America. Today, our AI agents analyze conversations, capture context, guide human agents, decide the next action, conduct customer conversations, orchestrate outreach, and help people complete payments and resolutions. They are connected, so what is learned in one interaction can inform what happens next. We are expanding this swarm of AI agents across more of the work financial institutions do: originations, document processing, back-office workflows, servicing, and other critical operations where money, identity, people, and regulation intersect. We are backed by Y Combinator, Accel, and Menlo Ventures, and work with 100+ financial institutions across North America. Listen directly from our CTO, Cofounder - Sangram Raje What You’ll Do Build and deploy LLM-powered AI agents (including voice agents) in production, designed for real-world use cases Own the end-to-end lifecycle of AI systems — from problem scoping and design to deployment, monitoring, and continuous iteration Design and optimize prompts, RAG pipelines, and evaluation frameworks to improve accurac
About Prodigal Prodigal is the connected AI platform leading financial institutions use to run their operations. We work with banks, lenders, credit unions, and other financial companies that lend money to people and manage those relationships over time. These institutions make millions of high-stakes decisions every day. Who should they reach? When should they reach them? What should they say or offer? When should a case move to a human? How should that change based on the borrower, the account, previous interactions, and the regulations involved? Getting those decisions right requires a deep understanding of the people, processes, rules, and edge cases behind them. Prodigal has spent the last eight years building that understanding. More than a billion interactions between financial institutions and their customers have shaped the intelligence, guardrails, and AI agents we now run in production across North America. Today, our AI agents analyze conversations, capture context, guide human agents, decide the next action, conduct customer conversations, orchestrate outreach, and help people complete payments and resolutions. They are connected, so what is learned in one interaction can inform what happens next. We are expanding this swarm of AI agents across more of the work financial institutions do: originations, document processing, back-office workflows, servicing, and other critical operations where money, identity, people, and regulation intersect. We are backed by Y Combinator, Accel, and Menlo Ventures, and work with 100+ financial institutions across North America. Listen directly from our CTO, Cofounder - Sangram Raje What You’ll Do Build and deploy LLM-powered AI agents (including voice agents) in production, designed for real-world use cases Own the end-to-end lifecycle of AI systems — from problem scoping and design to deployment, monitoring, and continuous iteration Design and optimize prompts, RAG pipelines, and evaluation frameworks to improve accurac
About Us At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Team This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market , shaping how LangChain is adopted in the field and feeding real-world insights back into the p
What We Do: Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact. Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection. Huntress now secures more than 5M endpoints and 16M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other. Reports to: Director, Engineering Location: Remote US, Only Compensation: $165,000 to $190,000 base plus bonus and equity What You’ll Do: Huntress is building an Agentic SOC. When our detection pipeline raises a signal, an LLM-based agent picks it up and investigates it end-to-end. It gathers telemetry across our products, reconstructs what happened, and makes a well-documented determination about whether the activity is malicious. Over time, it will take on more of the work itself, growing from resolving routine cases to acting fast when it finds an attack and handing analysts cases with the evidence already assembled. This system is meant to augment our analysts, not replace them. It takes the high-volume, repetitive work off their plates so they can focus on complex cases and hands-on keyboard intrusions where human expertise matters most. It also reduces toil in
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. About the role As a Senior Backend Engineer, you will design, implement, and evolve product capabilities while solving high-scope backend problems and influencing the technical and product direction of our teams. You will move beyond "assigned work" to actively improve the quality, reliability, and performance of our systems. You will work across product, frontend, infrastructure, data, and security boundaries, making sound architectural trade-offs, communicating complex ideas clearly in an asynchronous environment, and helping define the standards for a high-scale, global product. Why you’ll love this role High Impact: You aren'
The Role As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. You understand the relevance and application of ML & AI within a range of use cases important to the digital native customers in the Fintech space The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability
About the role We're looking for a Technical Lead Manager (TLM) to lead our CI/CD team , the group that owns how every Chime engineer builds, integrates, and safely ships code. Your team owns the integration and delivery surface: source and code intelligence ( GitHub , Sourcegraph ), continuous integration and build ( CircleCI , Qlty ), artifacts ( Artifactory ), and the release-safety layer that gets changes to production without breaking it. Your team's mission is continuous, safe, reliable, and efficient integration and delivery of features. Every merge and every deployment at Chime runs through what your team builds. This is a player-coach role . Under Chime's Builder Operating Model, the TLM is a single accountable owner at the team level. You own both delivery and people for a small team, and you stay hands-on in the codebase. You'll spend about 40%+ of your time building , authoring PRs that land in production, with the remainder split across people management, planning, and other business processes. You'll lead a team of 4 engineers, own the roadmap for a high-leverage platform surface, and be directly accountable for the reliability of the pipelines and release systems in the critical path of every Chime team. You're expected to use AI coding agents and workflows to keep planning, operations, and delivery overhead low so you can stay in the code and operate the team. In this role, you can expect to Build and ship, hands-on. Author and review PRs that land in production. Own the team's technical direction, architecture, and quality bar; partner with senior ICs and lead technical design discussions and technical planning. Lead and grow the team. Own full people management for the team: 1:1s, career coaching, performance feedback, promotion decisions, and hiring. Build an inclusive, high-trust team and own its health and engagement. Mentor engineers toward Staff or a future TLM path. Own the CI/CD platform. Set direction and delivery for the build and in
TEGNA Inc. helps people thrive in their local communities by providing the trusted local news and services that matter most. With 64 television stations in 51 U.S. markets, TEGNA reaches more than 100 million people monthly across web, mobile apps, streaming, and linear television, while also maintaining a strong global presence in India with offices in Bangalore and Chennai that support technology, product, and business operations initiatives. Together, we are building a sustainable future for local news. Senior CRM Data & AI Developer Position Overview TEGNA is looking for a Senior CRM Data & AI Developer to join the dynamic engineering team. We are looking for a Senior CRM Data & AI Developer to integrate our CRM platform data with our Snowflake data warehouse. You will analyze and map the migration of CRM data into our Snowflake-based customer data platform and put AI solutions, including agent-based workflows, to work inside our CRM and web applications. As we build AI agents that integrate seamlessly with the CRM, you'll also create the user interfaces that bring them to sales users. You will bridge the functional and data gaps between the CRM platform and our AI and data team, turning business needs into clean, well-governed data and working AI features that sales users can rely on every day. What You’ll Do • Bridge CRM and AI. Act as the CRM platform subject-matter expert for the sales AI and data team, explaining data models, entities, and business processes and turning requirements into technical solutions. • Lead the CRM data migration. Analyze, map, and implement the migration of CRM data into a customer data platform, including data analysis, identity resolution, mapping, and data mastering. • Build CRM UI. Build intuitive CRM user interfaces, custom components, and workflow automation that bring data and AI insights to end users. • Integrate AI solutions
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