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ARB Buildcon Pvt. Ltd. is hiring! Position: Civil Billing Engineer Experience: 4 5 Years Location: Ahmedabad Skills: Client Billing, RA Bills, BOQ Preparation, Quantity Estimation, Rate Analysis, AutoCAD, MS Excel, and Billing Documentation. Interested candidates, please share your updated resume with your current CTC, expected CTC, and notice period.

RB Buildcon Pvt. Ltd. is hiring! Position: Civil & PEB Drafter Experience: 3 5 Years Location: Ahmedabad Skills: AutoCAD, Civil & PEB Drafting, RCC Detailing, GA & Fabrication Drawings Interested candidates, please share your updated resume with current CTC, expected CTC, and notice period.

To strengthen the CAD-BSO team's capability in managing Accounts Payable (AP), Commercial Administration (CAD), Billing, and related support activities for the Australia business by onboarding a resource who can effectively handle operational responsibilities, ensure seamless stakeholder coordination, maintain process efficiency, and support business continuity during current and future workload requirements. Source: Adani Group | Job ID: 54682

Location: Remote Orca is expanding into new product verticals, bringing a new class of regulated assets on-chain with the compliance infrastructure and liquidity primitives to make them actually work. Our ambition reaches beyond becoming the leading provider of financial primitives in crypto—we aim to reshape the foundation of finance itself. If you are someone who is tired of just working another job and wants to build something meaningful, then we invite you to join our team. We’re always looking for talented individuals to join our growing team. If you think your skills can contribute to Orca's mission, but don’t see a specific role that matches your expertise in our current open positions, we’d love to hear from you. By submitting your resume here, you’ll be considered for future opportunities that align with your background and interests. If there’s a potential fit for an existing or upcoming opportunity, our team will get in touch. While we’d love to respond to everyone, we’re unfortunately unable to provide individual updates on all open applications. What Orca offers Competitive Salary. Bonus AND Token allocation. Flexible work schedule. Home office stipend. Wellness stipend. Opportunity to co-work with the team multiple times a year from at different locations around the world, fully covered by Orca. Option to work remotely or from Orca’s office in New York City. Paid subscriptions to GitHub Copilot, ChatGPT, or other tools that make you more productive. About: https://orca.so Twitter: https://x.com/orca_so Discord: https://discord.orca.so Podcast: https://orcapod.orca.so Orca is an equal opportunity employer.

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds the foundations for agentic systems capable of operating at scale in complex production environments. Current bets span agents that run autonomously at scale, context and memory layers that make those agents more intelligent over time, and tools that help customers build and validate AI-native services in production. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do Lead and develop a team of engineers and applied scientists focused on building the foundations for agents operating at scale Work closely with product managers, research teams, and cross-functional partners to shape the team's bets from initial framing through to broader adoption, with a clear definition of success criteria at each stage Own end-to-end delivery of high-quality AI systems, from early research exploration to production-grade reliability, with high standards for operational excellence, system reliability, and technical quality Navigate the unique challenges of shipping AI-powered products: balancing quali

We are looking for a talented engineer to lead evaluation of startup acquisition opportunities in the AI, cloud and security space. You will drive product evaluations, prepare and manage technical architecture discussions with target groups in Product and Engineering and provide roadmap suggestions for M&A and investments for Datadog. You will be a key partner to Datadog’s C-level leadership and highly visible at the most senior levels of Datadog. The role is reporting into the Senior Director of Product Strategy and falls within the Product organization. We are looking for an innovative and strategic thinker who is passionate about the latest tech being developed by startups in the cloud, AI and security space. The ideal candidate enjoys researching and evaluating new technologies, works effectively with cross-functional teams, and communicates opinions concisely to our leadership team. Broad understanding of relevant Cloud Technologies and deep understanding of the full coverage of Datadogs current offerings is necessary. The Corporate Development team is small and values authentic, strong-willed individuals who think creatively and proactively. This role leads technical due diligence from a product and architecture perspective across our acquisition pipeline. You'll scope and stand up proof-of-concept and sandbox environments to stress-test candidate products, then give an honest, unvarnished view of their quality and depth - the kind of assessment that holds up regardless of deal momentum. You'll assess technical architecture, flag the risks and open questions that matter most early, and turn that into a clear post-acquisition integration path. Working closely with engineering, you'll keep the evaluation focused on what's actually decision-relevant, then translate the findings into strategic recommendations for leadership and help carry the integration through by partnering with the right people on the other side. What You’l

We are looking for a talented engineer to lead evaluation of startup acquisition opportunities in the AI, cloud and security space. You will drive product evaluations, prepare and manage technical architecture discussions with target groups in Product and Engineering and provide roadmap suggestions for M&A and investments for Datadog. You will be a key partner to Datadog’s C-level leadership and highly visible at the most senior levels of Datadog. The role is reporting into the Senior Director of Product Strategy and falls within the Product organization. We are looking for an innovative and strategic thinker who is passionate about the latest tech being developed by startups in the cloud, AI and security space. The ideal candidate enjoys researching and evaluating new technologies, works effectively with cross-functional teams, and communicates opinions concisely to our leadership team. Broad understanding of relevant Cloud Technologies and deep understanding of the full coverage of Datadogs current offerings is necessary. The Corporate Development team is small and values authentic, strong-willed individuals who think creatively and proactively. This role leads technical due diligence from a product and architecture perspective across our acquisition pipeline. You'll scope and stand up proof-of-concept and sandbox environments to stress-test candidate products, then give an honest, unvarnished view of their quality and depth - the kind of assessment that holds up regardless of deal momentum. You'll assess technical architecture, flag the risks and open questions that matter most early, and turn that into a clear post-acquisition integration path. Working closely with engineering, you'll keep the evaluation focused on what's actually decision-relevant, then translate the findings into strategic recommendations for leadership and help carry the integration through by partnering with the right people on the other side. What You’l

The Assurance, Risk and Compliance (ARC) Initiatives team at MongoDB owns the governance and delivery of key cross-functional security risk and compliance initiatives. The team designs and executes programs that support compliance audits, risk assessments, common control frameworks, operating cadences, and executive reporting that strengthen the organization’s assurance, risk management and compliance objectives. The policy and controls governance pillar is responsible for the structure, standards and operating mechanisms that keep MongoDB’s security policies, standards, procedures, and controls governance processes current, aligned, auditable and scalable across the organization. This includes ownership of the policy lifecycle, common controls framework governance, issue management, and the review cadences and cross-functional coordination needed to maintain strong governance maturity and audit readiness. This role sits under the Assurance, Risk and Compliance function within the Global Security Office and reports to the Director of ARC Initiatives. This role will be based remotely in the United States Responsibilities: Scope of Ownership Policy governance program ownership, including policy lifecycle management, documentation standards, review and approval cadences, change tracking, and exception governance Controls governance ownership, including common controls framework lifecycle management, control harmonization, framework mapping, and processes that support audit readiness and scalable control oversight Governance over supporting systems and workflows, including Jira, GRC tooling, documentation repositories, and reporting structures, that enable consistent execution and visibility Issue management and remediation governance, including intake, triage, tracking, and reporting for timely closure of findings Executive-ready reporting and metrics for policy health, controls maturity, policy exceptions and broader program effectiveness Program Leadership Own

The MongoDB Query Execution Team is hiring software engineers who want to join us in developing a high performing, reliable and modular distributed query system. Our engineers work on implementing and maintaining execution algorithms, building new query language features, tuning database performance, and more to power our customers' critical workloads. This role can be based out of our Dublin office or remotely in Ireland. Relocation can be supported. Position Expectations Understand and improve current functionality of the MongoDB query engine Contribute high quality C++ code and give and solicit feedback in code reviews Identify, design, implement, test, and support new features related to query performance and robustness, query language enhancements, diagnostics for query performance problems, and integration with other products and tools Work constructively with peers to deliver excellent technical solutions Candidate Profile 5+ years of experience in systems programming Experience in databases and/or data management systems is a huge plus, but not a requirement Hands-on experience building industrial-strength software Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Experience with large code bases, preferably in C++, C, Rust or a similar compiled language B.Sc in Computer Science or similar field, or equivalent practical experience Interest in the theory and practice of database query engines. Hands-on experience or M.Sc./Ph.D in the domain is a plus Success Measures In three months you’ll have contributed to the development of a project slated for the next major version, as well as fixed a few bugs in a minor version of our latest stable release series In six months, you’ll have taken on code review responsibilities and are independently delivering complex functionality and squashing bugs independently In twelve months, you’re leading the development of a new major feature and are h

Every sales play, program change, funding update, and PRM release we build across MongoDB's partner ecosystem only creates value if the people who need to use it actually know how. We're looking for a Head of Partner Enablement to own that translation layer — end to end. This is a dual mandate: enabling our external partners (SIs, ISVs, and cloud partners) to sell, deliver, and support MongoDB effectively, and enabling our own internal partner organization (Sales Plays & Offerings, Partner Programs, Cloud & Hyperscaler Programs, and everyone else in the ecosystem function) to stay current on products, programs, and the frequent changes that come out of a fast-moving partner strategy. You'll report to the VP of Partner Strategic Operations and build the enablement function into the connective tissue for the entire partner organization — the team every other partner-facing role in this org relies on to actually land their work with the people who need it, inside MongoDB and out. We are looking to speak to candidates who are based in Dublin or London for our hybrid working model. What You'll Do Own the enablement strategy — both audiences Define and own a single enablement strategy that explicitly covers two audiences: external partners (SIs, OEMs, Resellers, ISVs, cloud/hyperscaler partners) and MongoDB's own internal partner organization Build the operating model, governance, and content standards that keep both tracks coherent, current, and tied to the same underlying source of truth — rather than running as two disconnected efforts Prioritize enablement investment based on business impact: which sales plays, program changes, or PRM releases most urgently need enablement behind them Enable external partners Own partner onboarding, certification pathways (including MongoDB's SI Associate and SI Architect tracks), and ongoing training content that keeps partners current on MongoDB products, sales plays, and programs Partner with the Sales Plays & Offerings

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. Our engineering team is growing rapidly, and we are looking for Engineering Managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Responsibilities: Manage a rapidly growing team of engineers developing user-facing Mapping experiences Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals Build teams that are collaborative, inclusive, and respectful of each other Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members Create plans for prioritizing technical and resourcing challenges in your organizat

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. Our engineering team is growing rapidly, and we are looking for Engineering Managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Responsibilities : Manage a rapidly growing team of engineers developing user-facing Mapping experiences Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals Build teams that are collaborative, inclusive, and respectful of each other Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members Create plans for prioritizing technical and resourcing challenges in y

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. To strengthen our efforts, we are hiring a Senior ML Engineer who will work end-to-end on creating and improving new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end. Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers – powered by an up to date map. Responsibilities: Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing proble

Role Description Dropbox is building the knowledge layer that connects content, context, and action. As AI moves from assistants to systems that act, the structure and stewardship of enterprise knowledge becomes the difference between AI that helps and AI that fails. This role owns the context layer our AI depends on: what it can know, what it can trust, and what it is allowed to act on. You will lead the central function, setting the strategy, architecture, standards, and operating model that make enterprise knowledge reliable, current, and permissions-aware for both human and AI use, while domain experts stay accountable for the accuracy of their content. AI capability changes quickly, and this role changes with it. What a model can interpret, how content needs to be structured for retrieval, and what a system can safely act on all shift as the technology moves. You will track those shifts, translate them into practical standards, and revise your own past decisions when the ground moves under them. This is the first role of its kind at Dropbox. You will partner with IT, Engineering, Legal, Privacy, and Security, and your decisions will show up directly in how AI performs across the company. Responsibilities Define the source-of-truth strategy for enterprise knowledge: which systems are authoritative, what is indexed centrally versus fetched live, what is eligible for AI use, and what is archived or excluded, informed by an assessment of the authoritative sources behind our highest-value workflows. Define the enterprise standards that make content AI-ready across structure, metadata, provenance, and access, including where semantic models or knowledge graphs are warranted and where they are not, and translate them into authoring patterns adopted across domains. Design the control model for AI actions, including eligibility rules, preconditions, approval boundaries, escalation paths, and rollback requirements, so systems that act on enterprise knowledge stay traceab

Role Description Dropbox is building the knowledge layer that connects content, context, and action. As AI moves from assistants to systems that act, the structure and stewardship of enterprise knowledge becomes the difference between AI that helps and AI that fails. This role owns the context layer our AI depends on: what it can know, what it can trust, and what it is allowed to act on. You will lead the central function, setting the strategy, architecture, standards, and operating model that make enterprise knowledge reliable, current, and permissions-aware for both human and AI use, while domain experts stay accountable for the accuracy of their content. AI capability changes quickly, and this role changes with it. What a model can interpret, how content needs to be structured for retrieval, and what a system can safely act on all shift as the technology moves. You will track those shifts, translate them into practical standards, and revise your own past decisions when the ground moves under them. This is the first role of its kind at Dropbox. You will partner with IT, Engineering, Legal, Privacy, and Security, and your decisions will show up directly in how AI performs across the company. Responsibilities Define the source-of-truth strategy for enterprise knowledge: which systems are authoritative, what is indexed centrally versus fetched live, what is eligible for AI use, and what is archived or excluded, informed by an assessment of the authoritative sources behind our highest-value workflows. Define the enterprise standards that make content AI-ready across structure, metadata, provenance, and access, including where semantic models or knowledge graphs are warranted and where they are not, and translate them into authoring patterns adopted across domains. Design the control model for AI actions, including eligibility rules, preconditions, approval boundaries, escalation paths, and rollback requirements, so systems that act on enterprise knowledge stay traceab