Design And Cost Estimation Head Jobs

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

Opportunity Overview: This is a unique opportunity to join a high-caliber software engineering team that is growing quickly. You will play a key role in building impactful healthcare technology on a modern technology stack, with a focus on our core data and AI platforms. Your work will focus on enhancing the platform's key features, while also balancing scalability, reusability, and performance. Role Overview: We're looking for a Staff Platform Engineer to serve as the technical backbone of our Engineering organization. You'll own the technical strategy, and delivery of our platform — spanning architecture, DevOps, SRE, security, Dev-ex. This is a hands-on staff level role: you'll set technical direction, drive cross-team alignment, and be the senior escalation point for platform challenges. What you’ll do: Drive platform reliability, scalability, security, and cost efficiency across all environments. Technical Leadership: Provide technical leadership for platform components, Influence the technical strategy and architecture of our cloud platform, from CI/CD pipelines to observability and incident response. Design and implement platform components and reusable integration patterns that minimize custom development efforts, reduce the time spent on repetitive tasks, and ensure that integrations scale across multiple healthcare systems Partner closely with Architecture, DevOps, SRE, and Security teams to deliver cohesive platform solutions Cross-Functional Collaboration: Work closely with product teams, and solutions architects to understand integration needs and ensure the platform meets current and future business requirements. Serve as a senior escalation point for infrastructure and platform incidents Establish frameworks for: AI governance and compliance. Observability of systems. Traceability of decisions and outputs. Ensure enterprise readiness with security, auditability, and reliability in production environments. Security & Compliance : Ensure all p

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack. About the Roles The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance. Together, they design and operate scalable compute and ingestion frameworks using technologies such as Spark, Flink, Kafka, Airflow, and modern lakehouse solutions, while also building abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners. In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence. As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash’s business-critical insights and real-time personalization capabilities. You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases. You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 2+ years of industry experience at our I4 level, 5+ years of industry experience at our I5 level Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in th

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

ABOUT THE TEAM The Data Modeling team builds and maintains the core data models and metrics that power decision-making across Mural. We are part of the Data Organization and focus on creating shared, reusable data models that represent key product and business concepts and are used across the company. Our work supports internal analytics, customer insight reports embedded in the product, and AI/ML model training. We partner closely with Product, Engineering, Data Platform, Business Analytics, Data Science, and Analytics Engineering to ensure the company is working from consistent definitions, high data quality, and reliable data availability. We are a small, high-leverage team focused on building durable data foundations rather than one-off solutions. YOUR MISSION You will own the delivery and evolution of Mural’s core data models and shared metrics, with a strong focus on data quality, reliability, and availability. This is a hands-on leadership role. You will not build stakeholder-specific data marts or ad-hoc analyses. Instead, you will focus on building foundational, reusable data models and metric definitions that support many use cases across the company. Your success will be measured by how widely trusted, consistently available, and broadly reused the data models and metrics you own are across teams such as Business Analytics, in-product insights, and ML. WHAT YOU'LL DO Own and evolve core data models and metrics: Define and maintain shared models for product usage, customers, accounts, and key business metrics that support analytics, in-product customer insights, and AI/ML model training Build and operate foundational data products: Stay hands-on building models using SQL, Python, and Spark in a modern lakehouse environment (e.g., Databricks), with strong attention to data quality, availability, performance, and cost Define shared semantics: Design and maintain shared metric definitions and semantic layers so data is interpreted consistently across teams an

Role Overview We are looking for a Senior FP&A Engineer to lead the design and implementation of enterprise planning solutions across Finance, Sales, and Workforce domains. This role will be part of a Global Finance Technology, partnering closely with onshore FP&A, RevOps, and other Business teams. You will play a key role in driving the organization’s transition to driver-based, integrated planning using platforms such as Pigment, Anaplan, and Workday Adaptive Planning, while ensuring scalability, governance, and high-quality delivery from India. We are looking to speak to candidates who are based in Gurugram or Bangalore for our hybrid working model. Key Responsibilities 1. Enterprise Planning Delivery Design and build scalable planning models across: Financial Planning (P&L, Cash Flow, Balance Sheet) Workforce Planning and Cost modeling Sales & Revenue forecasting (ARR, pipeline, bookings) Own end-to-end delivery working with the Product Manager : design → build → test → deploy → support 2. Model Development & Optimization Build multi-dimensional, driver-based models with strong focus on performance Develop scenario planning, versioning, and forecasting capabilities Optimize model size, calculation efficiency, and user experience 3. Platform Expertise Subject Matter Expertise in: Pigment Anaplan (Model Builder / Solution Architect) Configure workflows, security, and access controls Leverage platform-native capabilities vs over-customization 4. Data Integration & Automation Integrate planning tools with enterprise systems: ERP (NetSuite / Oracle) CRM (Salesforce) Data platforms Build and maintain automated data pipelines using SQL, APIs, or ETL tools 5. Stakeholder Collaboration (Global Model) Work closely with US / EMEA FP&A, IT, and Business teams Participate in requirement workshops and translate business needs into technical designs Provide regular updates, demos, and documentation to global stakeholders 6. Governance, C

About the Team API Multimodal builds the developer-facing products and infrastructure that bring OpenAI’s image, audio, and real-time model capabilities into the world. We are responsible for high-scale APIs for image generation, speech transcription, speech generation, and low-latency voice interactions. We partner closely with Research and Inference to bring frontier model capabilities to developers and use customer feedback to improve our models. About the Role As a software engineer on API Multimodal, you will build and operate the products and distributed systems behind OpenAI’s image, audio, and real-time APIs. You will work across model integration, API design, and production infrastructure to turn new research capabilities into reliable developer experiences. This hands-on role combines backend and systems depth with product judgment: you will own projects end to end, partner with Research, Inference, and Safety, and help make multimodal AI useful at scale. Model training experience is not required. In this role, you will: Design, build, and ship developer-facing APIs and backend services that serve frontier models. Architect low-latency streaming, request, session, and model integration systems that make complex multimodal interactions reliable and intuitive at scale. Work directly with Research to bring new model capabilities into production, shape the systems around them, and incorporate feedback from real-world developers and customers. Own the availability, latency, scalability, and cost efficiency of the services you build. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards. Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed syste

About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary Our team owns the foundational AI/GenAI platform services that power CVS Health's internal agentic and LLM-driven tooling — including LLM routing and cost governance infrastructure, internal developer tooling for AI-assisted software development, retrieval-augmented generation (RAG) capabilities, and orchestration tools for building and deploying agentic workflows. We sit at the intersection of platform engineering and applied GenAI: we're responsible for making it fast, safe, and cost-effective for engineering teams across the enterprise to build with LLMs, while navigating the compliance realities of operating in a healthcare environment (PHI/PII handling, HIPAA, BAA requirements with model providers). This role will design and build core platform services — spanning areas like auth, quota/cost management, observability, and routing policy — and will help define what our next generation of foundational AI services looks like as the GenAI landscape evolves. The team is deeply senior and highly collaborative; we're looking for someone who brings genuine, self-driven enthusiasm for this space — someone who explores new ideas and tools because they're excited to, not because they were asked to — while working closely with the rest of the team to bring those ideas to life. Required Qualifications 5+ years of professional software engineering experience, i

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary CVS Health is seeking a Principal Software Engineer to lead the design and delivery of enterprise-scale Generative AI solutions that power next-generation healthcare experiences. This role goes beyond hands-on coding—you will define technical strategy, establish architectural standards, and guide multiple teams in building secure, scalable, and cost-effective AI platforms across AWS (Bedrock) and Google Cloud (Vertex AI API). You will partner with product, security, compliance, and enterprise architecture teams to ensure solutions meet business objectives, regulatory requirements, and performance goals. The ideal candidate combines deep technical expertise with leadership skills—capable of influencing cross-org architecture decisions, mentoring engineering teams, and driving responsible AI practices in production. Key Responsibilities Lead end-to-end platform delivery of highly scalable, secure AI services and applications leveraging AWS Bedrock (Foundation Models, Knowledge Bases, Agents, Guardrails) and Google Cloud Vertex AI (Gemini via Vertex AI API, Agent Builder, Vector Search, Search & Grounding) Architect and implement Retrieval-Augmented Generation (RAG) solutions, integrating proprietary data from sources like Amazon S3 and Google Cloud Storage/BigQuery, and using Bedrock Knowledge Bases and/or Vertex AI Search & Groundi

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deep

About Pinecone Pinecone is the knowledge infrastructure for AI at scale. Its leading vector database and knowledge engine, Pinecone Nexus, power accurate, performant AI applications for more than 9,000 customers and 800,000 developers worldwide. Pinecone's mission is to make AI knowledgeable. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. About the Team and Role: We are hiring a senior/staff software engineer to help design and build core components of our next-generation knowledge retrieval system built for the AI era – search and retrieval infrastructure that powers high-quality, scalable, and enterprise-grade agentic systems. You’ll build the framework that allows our customers to connect knowledge–synthesized from structured and unstructured data–to modern LLM-powered applications, leveraging the world’s best-in-class vector DB supporting semantic search and hybrid retrieval. This role is ideal for someone who loves backend system architecture, distributed systems, and applied AI infrastructure. It is a high impact role with significant ownership across architecture, performance, and system reliability. Responsibilities: Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation Design and build optimized indexing pipelines for structured and unstructured data Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration Improve retrieval quality through evaluation and observability frameworks Design APIs for internal and external user and agentic consumers Optimize latency, throughput and cost across large-scale inference and retrieval workloads Drive technical direction for reliability and security What You’ll Bring to the Table: To thrive in this role, you don't need to check every single box, but you should be deep

ABOUT THE ROLE Peloton Electrical Engineers are responsible for the architecture, design, and testing of hardware systems for Peloton products. This early-career position requires working collaboratively with engineers and engineering managers to support product improvement and development initiatives across the entire product lifecycle, from new product introduction through sustaining engineering. As the team is highly dynamic with an exciting product roadmap, you will play a key role in ensuring electrical design robustness, manufacturability, time to market, and cost goals are all met. You will work multi-functional with many teams including Program Management, Product Management, Operations, Quality, Mechanical Engineering, Firmware Engineering, and Industrial Design. YOUR DAILY IMPACT AT PELOTON Under the supervision of senior engineers and project leaders, develop and support product subsystems, adhering to department and company standards and processes Observe and execute on engineering requirements rigorously Write and execute clear test plans at the design and production phases Troubleshoot and solve performance problems during development and in production Efficiently write and archive test reports Clearly document and communicate your work to senior engineers and technical leads Use data to drive engineering decision making Create and manage engineering changes for updates and improvements to existing products Collaborate with adjacent development teams to ensure design success, including compliance, firmware, and mechanical Work with drafting team to ensure appropriate product definition and design controls Communicate with outside vendors and partners effectively Travel throughout Asia and to/from the USA is expected to be 10%-15% YOU BRING TO PELOTON Bachelor’s degree in Electrical, Electronics, or Systems Engineering (Master’s degree preferred) Previous internship or similar work experience as an engineer in a design/develo

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About Dynamic Tables Dynamic Tables (DTs) are Snowflake's declarative streaming transformation primitive. Customers define a SQL query and a freshness target; Snowflake handles the rest: orchestrating refreshes, maintaining snapshot consistency across a DAG of dependencies, and automatically incrementalizing the computation so that cost scales with what changed. Dynamic Tables is one of the fastest growing products at Snowflake and is a core part of Snowflake’s Data Engineering strategy. The Dynamic Tables performance team is responsible for making incremental refresh fast, predictable, and cost-efficient across increasingly complex query shapes. As a Staff Engineer on this team, you will own the technical direction for critical performance initiatives and be a force multiplier for the engineers around you. What You'll Do Lead the design and implementation of performance improvements to the incremental view maintenance engine, including multi-join incrementalization, novel incrementalization semantics, incremental window functions, and stacked operations. Help define the roadmap for the incremental view maintenance engine, identifying key performance, scalability, and correctness milestones, prioritizing high-impact enhancements, and aligning technical investments with prod

Job Description The Applications Development Senior Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities. Responsibilities: Conduct tasks related to feasibility studies, time and cost estimates, IT planning, risk technology, applications development, model development, and establish and implement new or revised applications systems and programs to meet specific business needs or user areas Monitor and control all phases of development process and analysis, design, construction, testing, and implementation as well as provide user and operational support on applications to business users Utilize in-depth specialty knowledge of applications development to analyze complex problems/issues, provide evaluation of business process, system process, and industry standards, and make evaluative judgement Recommend and develop security measures in post implementation analysis of business usage to ensure successful system design and functionality Consult with users/clients and other technology groups on iss