Senior Semantic Ai Analyst Jobs

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. Position Overview We are seeking a Senior Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field Strong background in machine learning, deep learning, and natural language processing Familiarity with training distributed training of neural networks for language and visual understanding What We Offer Opportunity to work on real-world problems at the cutting edge of AI research Opportunity to utilize research vision to innovate the entire company and make real-world impact Exposure to the full lifecycle of AI model development, from research to production Our compensation (base + equity) for this position is competitive with frontier AI labs About MongoDB

We're looking for an Engineering Manager to lead the Agent Context team in NYC. This team owns how Asana's AI systems search, retrieve, and reason over the work graph the search infrastructure, dense embedding pipelines, ranking systems, and evaluation frameworks that determine whether every AI experience at Asana is trustworthy or not. Your mission is to make retrieval comprehensive, reliable, and fast at enterprise scale, positioning Asana as the coordination and memory layer for the agentic enterprise. This is a high-leverage platform role: nearly every AI product at Asana - AI Teammates, chat experiences, agentic workflows depends on the systems this team builds. You will manage a team of senior engineers in New York collaborating daily with partner teams in San Francisco and Warsaw, and work alongside a dedicated Product Manager as your direct counterpart. This role is based in our New York office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday; most Asanas have the option to work from home on Wednesdays. What you'll achieve Own the technical direction and delivery of Asana's retrieval stack end to end: lexical and semantic search, dense embedding generation and backfill at scale, chunking and ranking strategies, and RAG comprehensiveness across the work graph. Build and operate the evaluation infrastructure that makes retrieval quality measurable recall/precision benchmarks, offline and online evals, and comparative testing across retrieval backends - so quality decisions are made with data, not vibes. Drive the cost, performance, and quality tradeoffs that define this space: when semantic search earns its infrastructure cost over lexical, how to hit latency targets without sacrificing recall, and how retrieval improvements compound into cheaper, faster downstream LLM calls. Set and enforce the bar for how other teams at Asana integrate with retrieval: clear ownership of embedding decisions, rollout g

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

Join the Atlas Search team to design and develop the next generation of Semantic and Vector Search infrastructure. Atlas Search is a growing cloud service that allows users to execute complex search and vector search queries using the MongoDB Query Language. Our users can focus on relevance and data retrieval instead of the machinery needed to search data at scale. Our team is building a cloud-based distributed system responsible for the core components of search including data ingestion, performance, query language, query execution, for both relevance-based search and vector search. Our product is being adopted quickly and there are many interesting projects. This is a technical role where you will be responsible for the infrastructure and features enabling our at-scale cloud service powering vector and semantic search. We are looking to speak to candidates who are based in the San Francisco Bay Area for our hybrid working model. What You’ll Do Lead complex projects across the MongoDB ecosystem, for instance, development of a new Search deployment framework within the MongoDB managed cloud Set project level strategy, architect features, and lead projects to successful execution Identify, design, and implement features enhancing our reliability, performance, security and efficiency Perform code reviews with peers and make recommendations on how to improve our software development processes Influence and grow team members through active mentoring and leading by example What We Look For 5+ years experience in data management/search systems, ideally with a strong distributed systems and infrastructure background Experienced in the development and maintenance of concurrent, stateful services Eager to shape the technological direction of a complex system and have the ability to lead initiatives through collaboration with others Experienced in writing features, debugging and optimizing multithreaded applications written in Java Familiarity with LLM

Senior Product Manager - Search Datadog’s Search team helps users – both human and agents – find answers to their questions. Search is a critical function in Datadog, and touches many product surfaces: the query editors in product homepages and dashboards, search bars for finding relevant assets, the global cmd+k navigation search, and the MCP tools that our Bits AI agent uses to respond to natural language prompts. Search is a full-stack team: owning user-facing search components, backend search ranking systems, and machine learning models to produce recommendations. The Search team is relatively new, and still growing. We have recently built out agentic search tools, and we are looking for a leader to help us expand to ambitious orchestration systems that deliver accurate results, and proactive recommendations across both keyword and semantic search. Beyond this, you’ll have room to influence how Datadog thinks about Search as a strategic surface. What you’ll do: Define and deliver how Datadog's AI agents discover the right context and tools to answer natural-language questions accurately and at scale Stay on top of industry trends in UI and agentic search experiences and capabilities Collaborate with Applied AI teams to integrate ranking, personalization, and recommendation models that scale across both human and agentic users Define and monitor KPIs for search quality, adoption, and downstream impact on user productivity; use them to drive data-informed decision making Engage directly with customers and internal product teams to deeply understand search journeys across query editors, global navigation, and natural-language agent interfaces Who you are: You have experience with search, ranking, or recommendation systems You are familiar with or very interested in MCP servers and differences between human and agentic UX You have a sharp eye for design and strong opinions on the micro-interactions — keyboard navigation, autocomplete behavior, loading

About the Role We are seeking a Staff Enterprise Architect, Data to lead the strategy, design, and modernization of our enterprise data landscape. This role operates at the intersection of data architecture, engineering, and AI enablement, defining solutions to integrate our Data Lake and Data Warehouse across multi-cloud platforms. Over the next 12-18 months, you will enable self-service data access and natural language query capabilities for business users. You will architect Master Data Management and data lineage frameworks ensuring AI models operate on high-quality, governed data. You will also evaluate and implement AI-powered tools to automate data quality monitoring and enhance data security. We're looking to speak with candidates based in the San Francisco Bay Area for our hybrid working model. Key Responsibilities Data Strategy & Roadmap Design semantic layer architecture standardizing business metrics enterprise-wide. Define governance guardrails ensuring natural language queries access validated master data sources Develop Master Data strategy for Customer and Product domains (phases 1-2), Finance and People to follow. Define golden record requirements, stewardship models, and system-of-record hierarchy. Partner with business owners on master data governance Define cross-cloud data integration strategy and reference architecture. Specify patterns (federation, replication, abstraction layer) balancing performance, cost, and data freshness. Document trade-offs and recommend implementations for batch and near-real-time use cases Develop 12-24 month data architecture roadmaps for Finance, Sales, Product, and People. Identify capability gaps and recommend technology investments with business value and effort estimates Systems Design & Solution Leadership Evaluate AI-powered data observability platforms for quality monitoring, pipeline failure prediction, and data classification. Define requirements, lead vendor POCs, and establish integration patterns

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing , taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. About the Team: AI Search The AI Search team owns Bloomreach’s core search platform, serving hundreds of millions of queries per day across enterprise customers. We build and operate highly scalable, low-latency systems that combine traditional information retrieval with modern ML-driven ranking and semantic understanding — all in production at scale. This team sits at the intersection of systems engineering, search relevance, and applied ML , with direct impact on customer revenue and experience. The Role: As a Senior Staff Engineer , you will be a technical leader responsible for shaping the architecture and long-term evolution of Bloomreach’s Search platform. You will lead complex initiatives, set technical direction, and mentor engineers, while remaining deeply hands-on. This role is ideal for someone

The Opportunity This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it. We are looking for an experienced Senior/Staff Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma’s customer-facing data products. In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery. The Role At the core of Enigma’s product is our data, which makes both data science and delivery systems central to what we build. As a Senior/Staff ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You’ll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems. This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems. What You'll Do Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS Evaluate and evolve our search technology stack, driving technical design decisions across index

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language

Position Overview: We are looking for a Senior Software Engineer to drive technical excellence, architect complex systems, and elevate our engineering team. You will own critical technical decisions, lead major initiatives from conception to delivery, and set the standard for engineering quality across our products. As a senior engineer, you will architect and lead the development of sophisticated AI-enabled features and infrastructure. This includes designing MCP server architectures, building advanced RAG systems, implementing agentic AI workflows, and establishing patterns that scale across our product portfolio. You will combine deep technical expertise in both traditional software engineering and AI/ML to deliver production-grade solutions. What You'll Do Lead the design and implementation of AI integration infrastructure (MCP servers, orchestration layers, API gateways) Build sophisticated AI features including advanced RAG systems, agentic workflows, and multi-step reasoning Establish AI engineering best practices, security patterns, and quality standards Lead technical initiatives from requirements through production deployment Make critical architectural decisions balancing performance, scalability, cost, and maintainability Design AI evaluation frameworks and implement quality benchmarks Debug and resolve complex production issues across traditional and AI systems Required Qualifications Tech Stack Core: Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, Docker AI & Integration: Python, MCP, AWS Bedrock, LangGraph/Semantic Kernel, Vector Databases, RAG Core Technical Skills 5+ years professional development with proven track record of delivering complex systems Strong Node.js and JavaScript/TypeScript expertise Advanced React and frontend architecture skills Extensive AWS architecture experience Expert PostgreSQL database design, optimization, and performance tuning Deep understanding of microservices, distributed systems, and

We are looking for passionate technologists to join our Pre-Sales organization to ensure that our growth is grounded and guided by strong technical alignment with our platform and the needs of our customers. MongoDB Pre-Sales Solution Architects are responsible for guiding our customers and partners to design and build reliable, scalable systems using our data platform. Our team is made up of seasoned software architects and developers who take direct responsibility for customer success, including the design of their software, deployment, and operations. You'll work closely with our field partner leaders and play a key role in winning deals and driving the business forward. You'll be a trusted advisor to a wide range of users from startups to the world's largest enterprise IT organizations. This role can be based remotely in the Indian region. As an ideal candidate, you will have: 5+ years of pre-sales experience with enterprise software and technical aptitude Working knowledge and ability to code with one or more modern scripting languages (e.g. Python, Node.js, SQL) and/or popular programming languages (e.g. C/C++, Java, C#) Working knowledge of UI development with demonstrable skills in semantic HTML, modern CSS, and TypeScript, integrated with frameworks(e.g, Vue.js , React.js , Angular.js ). Should demonstrate working knowledge of using AI agents (e.g Cursor, v0, Lovable, Windsurf) to orchestrate UI designs and interfaces. Proficient in deploying applications to the Cloud with cloud best practices(DevOps) any one cloud provider preferable AWS. Experience with benchmarking, profiling and performance tuning of Database systems 3+ years of software development experience Excellent presentation and communication skills A Bachelor’s degree or equivalent work experience As an ideal candidate, you may also have: Experience selling databases and/or deploying applications with any of the major cloud providers Experience with database progra

Opportunity Overview We're hiring a Data Architect who will serve as a senior technical leader responsible for architecting the complete lifecycle data moves, transforms, and creates value across every product line we operate. You'll own the blueprint for our enterprise data lakehouse - setting the standards, governance, and strategy that elevate data from a byproduct of operations to the company's most valuable asset. We need someone who pairs deep mathematical and logical modeling expertise with a builder's instinct - someone who codes, prototypes fast, and proves out next-generation AI data architectures before committing the organization to them. This role would need experience with US healthcare domain data. What You'll Do Semantic Layer Governance: Set the technical standard and reference architecture for a universal semantic layer across multiple distinct data products, ensuring unified definitions of complex metrics and healthcare business entities across Architect the Enterprise Context Layer: Define, scale, and govern the global Enterprise Ontology (abstract domain maps, business entity classes, and entity-relationship rules) that serves as the backbone for Agentic AI systems. AI-Native Prototyping : Leverage modern AI-native development environments (such as Cursor, GitHub Copilot) to rapidly generate, iterate, and document blueprints for complex enterprise data schemas and metadata layers. Security & Compliance Leadership : Embed regulatory compliance (HIPAA, FHIR) and security principles into platform design. Partner with security and compliance teams to ensure architectural decisions support audit readiness and risk mitigation. Cross-Functional Collaboration : Partner with executive leadership, product management, and engineering to translate business requirements into scalable technical solutions. Communicate complex architectural concepts to both technical and non-technical stakeholders. ISMS roles and responsibilities Good knowledge of Informati

Build the infrastructure that keeps every NVIDIA chip aligned from first spec to final shipment. NVIDIA's Silicon Co-Design Group sits at the convergence of architecture, silicon, systems, and manufacturing. The System–Manufacturing Architecture (SMAC) team coordinates between system specifications and manufacturing test specifications from pre-silicon POR through production release across GPU, SoC, and CPU programs. When that alignment drifts, silicon faces the consequences: escapes, yield loss, and performance loss. We're hiring a Senior Manufacturing & System Co-Design Workflow Engineer to lead the methodology and infrastructure that maintains holistic, systematic alignment, at scale across the full portfolio. The strongest candidates in this role design the workflow before being asked to fix a program, and build the checks and automation that confirm alignment holds long after they've moved on to the next problem. What you’ll be doing: SMAC Workflow Methodology: Define manufacturing spec types, including schema and semantics, derived from system PORs and features. Own the methodology that governs how specification work gets structured, versioned, and validated across the program lifecycle. Production Python Pipelines & Automated Checks: Develop production-grade Python pipelines and automated checks that catch specification drift between system POR and manufacturing test programs ,ATE, SLT, BLT, L10+, before silicon exposes the discrepancy. The goal is that misalignments surface in the workflow, not on the tester. E2E Program Integration & TPM Attestation: Wire SMAC work into the end-to-end program spine, milestones, gates, and artifacts, and define explicit TPM-driven attestation when checks lag. Alignment can't be assumed; it must be proven at every stage. Agent-Ready Tooling & CI Infrastructure: Integrate tooling into an agent-ready

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Agent Gateway Team The Agent Gateway team owns the identity-aware infrastructure that connects enterprise AI agents to the tools, data, and services their organizations authorize. Every call from Claude, Agentforce, Codex, and internal/homegrown agents to a resource flows through us. We enforce authorization, isolate credentials, mint the right token per target, and produce the audit trails that security teams rely on. We are early in a rapidly evolving space. The standards for agent identity (MCP, OAuth token exchange, DCR) are being built under our feet. Our roadmap includes hardening the data plane for on-premises customer deployments, extending policy semantics beyond tool-level allowlists, adding native support for Agent-to-Agent brokered delegation, and scaling to tenants with thousands of virtual MCP servers. The Senior Software Engineer Opportunity Okta is looking for a Senior Software Engineer to help build the Agent Gateway. You will own features and components across the data and control planes, turning technical designs and product requirements into reliable production systems. Working alongside staff engineers, you will implement token exchange, request routing, credential resolution, and policy evaluation as agent identity specifications evolve. This is a hands-on software development role at the intersection of product, security, and infrastructure. You will ship services that handle agentic traffic reliably and performantly at scale. Wha