Staff BESS Electrical Design Engineer, EPC

Redwood Materials is seeking a Battery Energy Storage Systems (BESS) Electrical Engineer to join our EPC team. This role is central to the design of scalable, high-performance energy storage infrastructure for utility-scale and distributed applications. Our mission is to build a sustainable circular economy for lithium-ion batteries by transforming recycled materials into high-quality inputs for new batteries.

Responsibilities will include: 

• Lead electrical engineering efforts for utility scale lithium-ion BESS projects from concept (system sizing, layout) through construction. 
• Interface with utilities and ISO/RTOs to support interconnection studies/submittals, permitting, and compliance for new renewable and BESS projects. 
• Serve as the internal subject matter expert (SME) for technical challenges related to BESS.  
• Design AC and DC electrical systems for BESS using medium voltage transformers, inverters, DC combiners, energy managers, and battery modules. Specify and procure long-lead AC equipment. 
• Develop schematic diagrams, single-line diagrams, wiring schematics, raceway plans, grounding plans, and protection strategies for AC and DC systems. 
• Specify and evaluate components such as circuit breakers, contactors, fuses, disconnects, emergency power off (EPO), and metering devices. 
• Coordinate with civil, structural, fire & life safety, SCADA/telecom, geotechnical, and DC system design teams to produce complete IFC packages and technical specifications. 
• Ensure designs comply with applicable codes and standards such as NEC 705, NEC 706, IEEE 1547, UL 9540, NFPA 855, and local amendments. Lead code reviews and provide summary to internal teams. 
• Integration of BESS with grid infrastructure and other renewable and traditional energy sources.  
• Perform power system studies for short circuit, load flow, arc flash, and protective device coordination for AC and DC systems. 
• Serve as the Electrical Engineer of Record for assigned projects. 
• Maintain up-to-date knowledge of BESS technologies, codes, and industry trends.  
• Lead R&D efforts to perform feasibility analysis of using medium voltage DC distribution system for integrating BESS with other sources. 
• Provide CA support for RFIs, submittal reviews, change orders, and site inspections. 
• Coordinate with internal stakeholders and external consultants to track scope, schedule, and budget. 
• Prepare engineering cost estimates and project schedules in collaboration with project controls at various design milestones. 
• Perform QA/QC reviews of electrical designs and mentor junior engineers. 
• Contribute to internal design standards, templates, and best practices. 
• Manage project workload and ensure timely delivery of engineering documents. 
• Support strategic initiatives related to grid integration, renewable energy, and energy storage. 

Desired Qualifications: 

• Bachelor’s or Master’s degree in Electrical Engineering from ABET accredited program. 
• Licensed Professional Engineer in Nevada or eligible for reciprocity. Must get their PE in Nevada and South Carolina within 2 months of start date. 
• Minimum 5 years of experience in solar, energy storage, or microgrid sectors, with at least 3 years focused on BESS design and deployment. 
• Proven expertise in interconnection and regulatory compliance for BESS systems. 
• SME in knowledge of NEC 705, NEC 706, IEEE 1547, UL 9540, and NFPA 855.  
• Advanced proficiency in: 
• Microgrid and hybrid power systems modeling tools using HOMER or similar 
• Power system modeling using ETAP, SKM, or similar 
• AutoCAD/Revit, Navisworks, Bluebeam, Microsoft Office 
• Preferred proficiency in: 
• Transmission-level load flow and stability using PSSE and PSLF 
• Electromagnetic Transient Simulations using PSCAD, EMTC or similar 
• SEL Relay Settings using SEL AcSELerator or equivalent 
• Design of HVDC systems and converter station 
• Strong understanding of energy storage use-cases including peak shaving, load shifting, demand response, and frequency response. 
• Highly motivated, proactive, and detail oriented. 
• Ability to communicate effectively through verbal, written, and visual formats. 

Staff Electrical Design Engineer, EPC

The Staff Electrical Engineer is responsible for the end-to-end electrical design of industrial, offices, and lab facilities across multiple locations. The role holds full ownership of electrical deliverables — from concept through construction — across a diverse range of project types including hazardous occupancy, recycling facilities, office and labs, warehouse environments, and 34.5 kV/24.9 kV site infrastructure. The engineer is expected to operate with a high degree of independence, serving as Electrical Engineer of Record on assigned projects while coordinating across multiple disciplines to deliver code-compliant, construction-ready packages on schedule and within budget. This position requires a licensed Professional Engineer who is not only highly skilled at performing complex engineering calculations but also motivated, detail-oriented, and capable of communicating effectively at all levels — from field teams to executive stakeholders.

Responsibilities will include:

• Design and own a wide range of electrical systems — including medium voltage (up to 34.5 kV) feeds, low voltage power distribution, lighting, raceway, grounding, and communications. 
• Serve as Electrical Engineer of Record and responsible for producing permit and construction drawings. 
• Perform power system studies including short-circuit analysis, arc flash calculations, and protective device coordination using SKM or ETAP to ensure safe and code-compliant designs. 
• Perform cable ampacity calculations using AmpCalc or similar software to optimize cable size instead of using prescriptive tables from National Electrical Code (NEC). 
• Lead multi-discipline coordination with architectural, civil, structural, mechanical, fire & life safety, and other design teams to produce complete Issue for Construction (IFC) packages. 
• Review conceptual designs from manufacturing engineers and stakeholders to identify technical and financial risks. Prepare electrical specifications and conduct technical bid evaluations for designs produced by external design consultants. 
• Lead code analysis for NEC, IECC, and applicable NFPA standards across all project deliverables, and ensure designs meet all regulatory and compliance requirements. 
• Provide construction administration support including RFI responses, submittal reviews, change order management, and on-site inspections. Serve as the technical point of contact during construction and commissioning. 
• Prepare engineering cost estimates and project schedules, perform QA/QC reviews of electrical designs, and mentor junior engineers while contributing to internal design standards and best practices. 

Desired Qualifications: 

• Bachelor’s or Master’s degree in Electrical Engineering from ABET accredited program. 
• Licensed Professional Engineer in Nevada or eligible for reciprocity. Must get their PE in Nevada and South Carolina within 2 months of start date. 
• Minimum 10 years of experience in heavy commercial and industrial sectors, with evidence of exceptional ability. 
• Subject matter expertise in National Electrical Code (NEC), International Energy Conservation Code (IECC),  and relevant National Fire Protection Association (NFPA) standards with demonstrated ability to lead code analysis and apply requirements across complex, multi-discipline projects. 
• Advanced proficiency in Revit MEP, AutoCAD, Navisworks, Bluebeam, and SKM or ETAP for design production, clash detection, document review, and power system studies. 
• Advanced proficiency in AmpCalc or similar for cable ampacity calculations. Ability to perform photometric studies using lighting design software such as Visual or AGI and make decisions on optimal lighting levels for projects. 
• Strong analytical and problem-solving abilities, with the capacity to independently manage multiple concurrent projects, prioritize tasks effectively, and deliver high-quality engineering documents on schedule. 
• Ability to travel to project sites for construction administration, commissioning support, and field issue resolution, with flexibility to adjust availability based on project phase demands. 
• Excellent communication skills — verbal, written, and through drawings/sketches — with the ability to collaborate across disciplines and interface confidently at an executive level. 

Staff Mechanical Design Engineer, EPC 

Redwood Materials is hiring for a Staff Mechanical Design Engineer to join our Engineering, Procurement, and Construction team. This role is at the center of our activities focused on creating a sustainable circular economy for lithium-ion batteries by transforming recycled materials into battery materials for new lithium-ion battery production. 

Responsibilities will include: 

• Serve as Mechanical Engineer of Record on projects (Hazardous occupancy, clean and dry spaces, chemical process / industrial plants), responsible for mechanical / plumbing deliverables (specifications, calculations, permit / construction documents). 
• Design ownership for a wide range of mechanical and plumbing systems including, but not limited to: industrial/non-potable water, HVAC systems (labs, offices, industrial plants), process heating / cooling systems humidifiers, dehumidifiers, abatement systems (dust collectors, scrubbers), cooling towers, fans/pumps, plumbing, etc. 
• Review conceptual designs from developing Engineers and identify technical and financial risks. 
• Responsible for designing/reviewing mechanical engineering deliverables with respect to code compliance and ensuring design maintains the highest level of quality. 
• Develop and improve project workflows and standards to ensure each design is consistently excellent. 
• Participate in on-field construction and commissioning activities by serving as the point of contact for technical questions and real-time issue resolution. 
• Multi-discipline collaboration on the development of equipment general arrangements, P&IDs, isometrics, tie-in lists and material takeoffs. 
• Travel to project site and meetings as needed. 

Desired Qualifications: 

• Bachelor’s Degree in Mechanical Engineering or an equivalent discipline. 
• Licensed Professional Engineer with NCEES record with ability to apply for NV and SC 
• 7+ years of work experience in HVAC and Plumbing/FP design. 
• Expert familiarity with ICC including International Energy Conservation, Mechanical, Plumbing and Fire Protection Codes, NFPA standards, SMACNA duct construction standards, ACGIH Ventilation Practices and ASHRAE 
• Working knowledge of designing the following equipment types: condenser fluid heat rejection systems, chillers, boilers, air handling units, air and water source heat pumps, dust collectors, humidifiers, dehumidifiers, fans, and pumps. 
• Working knowledge or experience with the following is preferred: Abatement systems (thermal oxidizers, dry and wet scrubbers), Heat Exchangers (shell/tube, plate/frame, brazed fin), Control Valves and Instrumentation, and Heat Recovery Systems. 
• Working knowledge of writing sequences of operation for HVAC and chilled water systems. 
• Ability to specify ductwork material and size for various ducted exhaust systems and pressure classes. 
• Ability to specify pipe material and size for various thermal hydronic systems. 
• Ability to create or edit construction specifications covering mechanical, process piping and plumbing systems. 
• Proficient in the use of Revit and AutoCAD. Experience sourcing and specifying mechanical equipment and executing RFP process. 
• Strong experience with engineering software packages: Pipe-Flo (or other hydraulic modeling application), Caesar II, AspenTech applications and/or Applied Flow Technology applications, Carrier HAP, Trane Trace, Navisworks, Bluebeam. 

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the team 

The Capacity & Efficiency team sits inside Anthropic’s Compute organization and owns the cost, utilization, and attribution story for non-accelerator infrastructure — the network, compute, and storage backbone that moves petabytes between training clusters, inference fleets, and object storage across clouds and regions. The scale is real, the spend is large, and the efficiency levers are still mostly unpulled.

We work alongside the Systems Networking team (who build and operate the fabric) and the Observability team (who own the telemetry platform). This role lives at the intersection: you’ll use deep networking knowledge and rigorous measurement to figure out where and how bandwidth, latency, and dollars are being used, find optimization opportunities and land them.

About the role

We’re looking for a network engineer who thinks in metrics first. You understand spine-leaf fabrics, BGP, SDN overlays, and cloud interconnect products well enough to build them. You will instrument them, model their cost-per-bit, and squeeze out the inefficiency, while ensuring we can move the bits to the right places in the most efficient manner. You’ll own the observability and efficiency surface for Anthropic’s network: from per-flow telemetry on backbone routers, to cost attribution that tells a research team exactly what their checkpoint sync is costing.

This is a hands-on IC role. You’ll write code (Python, Go), build dashboards and model capacity. You’ll also influence architecture: when the data says a traffic pattern is pathological, you’ll be in the room root causing it and fixing it. 

You will be working across three areas: network telemetry, observability and cost modeling and attribution. We expect you to be strong in at least two and willing to grow into the third. If you're a telemetry-first engineer who's never built a chargeback model, or a traffic engineer who hasn't shipped eBPF probes, apply anyway and tell us which axis you want to grow on.

What you’ll do

• Build the network observability stack. Design and deploy telemetry pipelines — sFlow/IPFIX, gNMI streaming, eBPF host probes — that turn packet counters into per-flow, per-tenant, per-workload cost and utilization data. Own the SLIs for backbone and DCN fabric health.

• Hunt for efficiency. Analyze inter-region traffic patterns, identify hot links and stranded capacity, and quantify the dollar impact. Build the models that tell us whether we should buy more capacity, or move the workload.

• Own QoS and traffic engineering. Design and operate traffic classification, marking, and shaping across the backbone. Make sure bulk checkpoint transfers don’t starve latency-sensitive inference, and that we’re not paying premium cross-region rates for traffic that could take the cheap path.

• Drive cost attribution. Tie network spend — egress, interconnect ports, transit, optical leases — back to the teams and workloads that generate it. Make network cost a first-class input to capacity planning and workload placement decisions.

• Influence decisions you don't own. A large fraction of this role is convincing other teams to act on what your data shows: making the case to research that a traffic pattern needs to change, to finance that an interconnect tranche is worth buying, to Systems Networking that a QoS policy needs rewriting. You'll partner closely with Systems Networking on fabric architecture and Observability on telemetry platform integration, but the cost and efficiency wins will come from moving teams that don't report to you.

• Automate. Extend our intent-based network configuration systems and write the tooling that turns your efficiency findings into safe, reviewable, and impactful changes.

You may be a good fit if you

• Have 5+ years operating large-scale production networks — data center fabrics (spine-leaf, Clos), backbone/WAN, or hyperscaler-adjacent environments. 

• Are genuinely fluent across the stack: BGP (including policy and communities), ECMP, VXLAN/EVPN or equivalent overlays, QoS (DSCP, queuing, shaping), and L1/optical basics (DWDM, coherent, LAGs).

• Know at least one major CSP’s networking model deeply — AWS (VPC, TGW, Direct Connect, Gateway Load Balancer) or GCP (Shared VPC, Interconnect, Cloud Router, Network Connectivity Center) — and understand how their overlays interact with physical underlays.

• Have built or operated network telemetry at scale: streaming telemetry (gNMI/OpenConfig), flow export (sFlow, IPFIX, NetFlow), or eBPF-based host-side instrumentation. You can reason about sampling, cardinality, and storage tradeoffs.

• Comfortable writing Python or Go to build tooling, telemetry pipelines, infrastructure-as-code, config management for network devices and automation, that you’ll ship to production.

• Think quantitatively by default. You reach for a notebook or a Grafana query before you reach for an opinion, and you can turn messy counter data into a defensible cost model.

• Communicate crisply. You can explain to a finance partner why a 10% egress reduction matters, and to a network engineer why a specific ECMP imbalance is costing real money.

Strong candidates may also have

• SRE experience for large-scale network infrastructure — designing for reliability, defining SLOs/SLIs for network services, capacity planning with error budgets, and incident response for network-impacting outages at scale.

• Background on a cloud provider's networking team or a cloud networking product team — building or operating the interconnect, backbone, or SDN control plane from the provider side, not just consuming it as a customer.

• Familiarity with AI/ML infrastructure traffic patterns like collective communication (all-reduce, all-gather), checkpoint/weight transfer, inference serving, and how these stress networks differ than traditional workloads in terms of burst behavior, flow synchronization, and bandwidth symmetry.

• Experience with HPC fabrics like InfiniBand, RoCE v2, lossless Ethernet, or custom high-radix topologies and an understanding of how job placement, congestion management, and adaptive routing interact at scale.

• Background in traffic engineering for large backbones and the operational judgment to know when TE is worth the complexity.

• Hands-on time with multi-cloud connectivity: cross-cloud peering, private interconnect products, and the billing models that come with them.

• Experience building cost/chargeback systems for shared infrastructure, or FinOps exposure in a large cloud environment.

Representative projects

• Build a per-flow cost attribution pipeline that traces every byte of cross-region egress back to the team and workload that generated it

• Design QoS policy for the private backbone that prevents bulk checkpoint transfers from starving inference traffic

• Model whether it's cheaper to buy an additional 1.6Tb interconnect tranche or to re-route traffic through existing capacity

• Instrument DCN fabric utilization with streaming telemetry and build the Grafana dashboards that become the team's source of truth for network observability 

Why this role, why now

Anthropic’s network footprint is growing faster than our ability to reason about it. We’re turning up tens of terabits of private backbone capacity, peering across clouds, and moving model weights that keep getting larger. The efficiency opportunities are enormous and largely untouched — this is a chance to build the measurement and optimization layer from the ground up, with real budget impact and direct influence on how Anthropic’s infrastructure scales.

Staff High Voltage Electrical Engineer, EPC

Redwood Materials is seeking a Staff High Voltage Electrical Engineer to join our EPC team. This role is central to the design of high voltage electrical infrastructure to support our mission. Our mission is to build a sustainable circular economy for lithium-ion batteries by transforming recycled materials into high-quality inputs for new batteries. 

Responsibilities will include: 

• Lead the design of high voltage AC electrical systems, specifically for industrial substations (69kV to 345kV) and their integration with upstream transmission lines and downstream MV distribution
• Review and evaluate the design of existing substations to provide recommendations for improving reliability and stability
• Develop single-line diagrams, physical layout and design, protection and control systems, relay design and coordination, and grounding plans for substations
• Perform grid simulation and stability studies using industry standard tools such as PSSE, PSLF, PSCAD, ASPEN OneLiner and similar software
• Interface with utilities and ISO/RTOs to support interconnection studies, permitting, and compliance for new renewable and BESS projects 
• Perform short circuit, load flow, and arc flash studies
• Develop relay settings using SEL AcSELerator or equivalent software
• Evaluate and select high voltage equipment including switchgear, circuit breakers, transformers, reactors, PTs, CTs, and protection relays
• Serve as Electrical Engineer of Record for assigned projects
• Lead code compliance reviews (NEC, IEEE, NESC, NFPA) and provide technical guidance to internal teams
• Collaborate with civil and structural engineers on substation layout, foundations, and site development
• Support facilities, construction and commissioning teams with field engineering, testing, and troubleshooting
• Review vendor submittals, RFIs, and shop drawings for technical accuracy
• Participate in technical bid evaluations and identify scope gaps
• Lead R&D efforts to perform feasibility analysis of using medium voltage DC distribution system for integrating BESS with other sources
• Independently manage high voltage design packages from concept through commissioning
• Coordinate with internal stakeholders and external consultants to align scope, schedule, and budget
• Prepare engineering cost estimates and execution schedules in collaboration with project controls
• Lead technical reviews and design optimization workshops
• Mentor junior engineers and contribute to team development
• Develop workflows, templates, and standards for high voltage design and simulation
• Support strategic initiatives related to grid integration, renewable energy, and energy storage

Desired Qualifications: 

• Bachelor’s or Master’s degree in Electrical Engineering from ABET accredited program
• Licensed Professional Engineer in Nevada or eligible for reciprocity. Must get their PE in Nevada and South Carolina within 2 months of start date
• Minimum 10 years of experience in high voltage electrical design, preferably in EPC environments
• Advanced proficiency in: 
• Transmission-level load flow and stability using PSSE and PSLF 
• Electromagnetic Transient Simulations using PSCAD, EMTC or similar 
• SEL Relay Settings using SEL AcSELerator or equivalent 
• Relay coordination and fault studies using ASPEN OneLiner or similar 
• Power system modeling using ETAP, SKM, or similar 
• AutoCAD, Navisworks, Bluebeam, Microsoft Office 
• Preferred proficiency in: 
• Design of HVDC systems and converter station 
• Strong understanding of protection and control systems, SCADA, and substation automation
• Highly motivated, proactive, and detail oriented
• Ability to communicate effectively through verbal, written, and visual formats
• Field experience in construction and commissioning of high voltage systems is highly preferred
• A passion for sustainability and making the world a better place!

About Bridge

We’re creating an entirely new payments platform, built with stablecoins, to simplify global money movement. Bridge enables faster, cheaper payments and borderless access to dollars via stablecoins. Through our APIs, businesses can send and receive funds across borders faster / cheaper vs. SWIFT and other fiat-only rails. Our virtual accounts enable international consumers and businesses to easily access, store and spend US dollars. Our payouts infrastructure enables platforms to disburse USD to anyone globally. We believe many trillions of dollars will move and settle through stablecoin payment rails. Bridge is pulling this future forward. 

We have a small team of people who have previously built financial infrastructure at some of the world’s leading companies (Coinbase, Stripe, Square, Brex, Upstart, DoorDash, Airbnb) and each and every one of them chose Bridge because they fundamentally believe that stablecoins will be a critical piece of financial infrastructure that allows for the improvement of global money movement.

About the Role

As an early member of the Bridge engineering team, you will be given the autonomy to work on projects that are truly global in scale and aim to give customers access to products they've never had access to. Many of the use cases that we work on today didn't exist several months ago and that's because our team is dedicated to constant improvement for our partners and end users. Our Engineers have outsized ownership over projects so if you are looking for increased autonomy working on a completely greenfield opportunity, Bridge is the place for you.

Responsibilities

• Ship software to build out our suite of API products. We’re an engineering and API-first company, and you will learn first-hand and contribute towards building highly reliable, performant, and mission critical infrastructure serving thousands of developers across the globe.

• Take sole ownership of projects, oftentimes without the support of Product Management, and liaise both internally with teams like Legal/Compliance and externally with our partners and developers.

• Look for constant improvements to our product offerings with the explicit goal of improving the experience for our partners and end users.

• Make effective tradeoffs that consider business priorities, user experience, and a sustainable technical foundation.

• Improve engineering standards, tooling and processes for the team and our broader org.

Qualifications

• We are open to hiring engineers at various levels of seniority (SWE through Senior Staff) but at a minimum we are looking for somebody with 5+ years of experience.

• Experience building backend systems with SQL databases. Experience with frameworks such as Rails, Django, Express or equivalent is a bonus.

• An enlarged sense of ownership and the ability to lead and influence the design and direction of our products.

• An ability to thrive in a fast paced environment.

• A growth mindset and a constant curiosity and fearlessness to dive into the unknown.

• An ability to write maintainable, well-tested, modular code, but also be pragmatic about moving fast.

• Excellent written and verbal communication skills, including the ability to write clear technical documentation.

• Past experience working on crypto or financial products a plus, and while not required, we do look for people who are very passionate about building in this space.

• Experience with building API products a plus, but not required.

• Experience working with blockchain or distributed systems a big plus

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Before Stripe, every growing internet platform had a payments team. Today, every growing internet platform has an Identity team. Identity verification has become core economic infrastructure for online businesses — enabling them to digitally verify their users' identities for fraud prevention, regulatory compliance, and trust and safety purposes.

At Stripe, we're building something more ambitious than a verification product. Our vision is to build the world's most trusted store of verified identities — a single, global, reusable, risk-scored representation of every individual who interacts with Stripe and beyond. This Identity Store becomes a platform with compounding network effects: more verifications enrich the store; a richer store produces better fraud signals; better signals mean lower friction for trusted users; lower friction drives more adoption.

Our product today serves millions of verifications per month for customers like OpenAI, Shopify, and WhatNot, and powers identity verification across multiple internal Stripe products including Fraud, Link, Connect, and Crypto. The problems ahead — adversarial AI and deepfake defense, networked identity infrastructure, progressive verification platforms, and low friction KYC APIs — sit at the frontier of what's possible in identity engineering.

What you’ll do

As a Staff Engineer on the Identity team, you will own the technical direction of one of Stripe's most strategically important product areas. This is not a role defined by task execution — it's a role defined by technical judgment, architectural influence, and the ability to turn an ambitious vision into a reliable, scalable system.

Responsibilities

• Own technical strategy — Define the architecture for Identity's core systems (Identity Store, headless verification platform, fraud detection infrastructure), make build-vs-buy-vs-partner decisions, and surface technical risks before they become customer-facing failures
• Lead 0-1 platform development — Architect net-new systems including the Identity Store, Networked Identity platform, and advanced fraud detection pipeline (behavioral biometrics, deepfake discriminators, adversarial training). Drive the evolution from a hosted-UI product to a headless-API and embedded-components platform
• Drive cross-functional alignment — Be the primary technical voice in roadmap and resourcing discussions. Partner with ML, product, legal, and engineering leads across Risk, Fraud, Link, Connect, and Crypto to ensure Identity's abstractions serve the full breadth of Stripe's product surface
• Raise the technical bar — Set engineering standards across ML, backend, mobile, and front-end; lead design reviews; and mentor senior engineers on the judgment needed to operate a high-stakes, externally-facing product
• Operate with ownership — Be accountable for reliability, scalability, and security of the systems you design — including the observability and alerting that catch model drift and fraud pattern shifts before customers do

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role.
• Experience leading engineering team(s) working on API design, abstractions, frameworks, or client libraries (e.g. building internal or external developer products). 
• Proven track record of delivering pragmatic solutions that accelerate business growth 
• Ability to adjust conversations from high-level discussions to detailed coding 
• Thrives on a high level of autonomy and responsibility 
• Clear and persuasive writing and in-person communication 
• Strong problem-solving skills, critical thinking, determination, and a growth mindset 
• Ability to work effectively with a diverse group of people, genuinely caring for each other and contributing to high level of psychological safety for all team members and partner
• Has experience in a range of software languages and frameworks. Examples of what we work with include:
• Languages: primarily Ruby and Typescript, but also Python, Scala, Java, Go, and SQL (Spark and Trino dialects)
• Frameworks: React, GraphQL Kafka, Protobuf, Airflow, Bazel, Temporal, 
• Others: Mongo, Splunk, Prometheus

Preferred qualifications

• Experience with identity verification, fraud detection, or trust and safety systems — especially systems with adversarial inputs at scale
• Familiarity with ML systems in production: model serving, training pipelines, observability, drift detection, and the feedback loops that keep models accurate under adversarial conditions
• Experience building platform products with multiple consumer types — internal platform teams and external developers — where API backward compatibility and abstraction quality are first-class concerns
• Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly
• Exposure to the technical stack we work with: primarily Ruby and TypeScript on the backend and web, Python for ML and data pipelines, with infrastructure spanning Kafka, Temporal, Protobuf, React, and distributed data stores
• Experience navigating ambiguity in a fast-moving organization — you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge

Why Stripe Identity

• The market is at an inflection point. The global identity verification market is growing at ~15% CAGR, from $12.5B in 2024 to $21.8B by 2028. Competitors have more features today — but none of them have Stripe's moat: payments signals, fraud network, consumer graph, and KYC data spanning the full financial ecosystem. We're building to win the next decade, not the last one.
• The problems are genuinely hard. Adversarial ML against deepfakes and face swaps. Distributed identity graph architecture with real-time freshness requirements. Progressive verification APIs that minimize friction without sacrificing fraud detection accuracy. These are unsolved problems — not just at Stripe, but in the industry.
• You'll work on systems that matter immediately. The verifications we run protect real users from real fraud. When our recall improves by 10 points, that's millions of dollars in prevented fraud losses for customers who rely on us. When our mobile SDK completion rate rises, thousands more legitimate users successfully onboard each month.
• The team is small enough that your judgment shapes the architecture. This isn't a role where you inherit decisions made five years ago. It's a role where the decisions you make in 2026 are the ones the team will build on through 2029.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Workflow Engine team provides critical infrastructure for Stripe’s business, by allowing engineers to write asynchronous, stateful workflows that are both reliable and fault-oblivious. Our platform abstracts away challenging distributed system complexities and enables engineers to focus on the critical business logic they’re responsible for. Workflows power products such as Stripe Capital, Billing, and Connect, as well as many mission critical control planes.

What you’ll do

As a technical leader on the Workflow Engine team, you will help guide our service platform’s asynchronous execution capabilities, making asynchronous systems easy to build, resilient, and scalable. You will care deeply about the productivity of the engineers using our systems and lead the engineering organization towards ensuring a thoroughly considered ergonomic developer experience.

Responsibilities

• Design, build, and maintain the core infrastructure used by all of Stripe’s engineering teams to asynchronously process financial data and transactions.
• Liaise with teams using this core infrastructure to ensure it meets their needs and expectations
• Debug production issues across services and levels of the stack, including managing an on-call pager rotation
• Plan for the growth of Stripe’s asynchronous infrastructure
• Analyze existing software for performance optimizations and quality assurance testing
• Mentor other engineers in the organization and review code
• Manage projects, including measuring impact and success of the project, and creating a maintenance and reliability plan for the future

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• Minimum 10+ years of engineering experience or equivalent combined work experience reflecting domain expertise 
• Demonstrated experience of leading initiatives spanning multiple teams and leveraging deep domain expertise to influence tech roadmap planning and execution
• Demonstrated ability to effectively collaborate across multiple teams and stakeholders to drive business outcomes
• Experience, mentoring, and investing in the development of engineers and peers

Preferred qualifications

• Demonstrated expertise with Temporal, Cadence, or other workflow orchestration systems.
• Expertise with tackling complex, distributed systems/infrastructure challenges at scale
• Deep familiarity with API design for large scale distributed systems
• User-centric orientation and track record for productizing elegant infrastructure solutions for complex problems

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Stream Compute team at Stripe builds and operates the infrastructure, tooling, and systems behind our Flink-powered stream processing systems. We're at the heart of several core asynchronous workflows, operating at significant scale and handling vast amounts of sensitive financial data. Our work powers intricate processes involving various critical financial operations and real-time analytics. We run globally distributed systems with high reliability and performance to meet Stripe's scaling, availability, and product needs, and we continually reduce operational toil by investing in automation and self-service tooling for upgrades, maintenance, and day-to-day operations. The team is distributed between Seattle, Toronto and remote locations.

What makes our team truly exciting is our commitment to our users: we ensure no event is dropped, state integrity is preserved, and support exactly-once processing as a first-class feature. Working at the intersection of real-time data processing and fintech innovation, we continuously push the boundaries of what's possible. Our focus on innovation, user experience, reliability, and compliance drives increased ROI and operational excellence, making us a crucial part of Stripe's success.

What you'll do

You'll help define and deliver the next generation of Stripe's Flink-first stream compute infrastructure—driving innovation to meet extremely high availability targets at global scale. Partnering with infrastructure engineers, adjacent platform teams, and the product orgs that depend on Flink every day, you'll set a long-term technical direction that scales with Stripe's growth while enabling reliable, efficient operations for years to come. You'll work on the hardest problems in operating Flink in production—state management, exactly-once processing, performance isolation, and automated recovery—so teams across Stripe can confidently build stateful stream processing applications on top of it.

Responsibilities

• Design, build, and operate stream compute infrastructure with Apache Flink at the center, alongside technologies like Kafka, Temporal, and AWS services
• Partner with product and platform teams across Stripe to understand requirements, unblock Flink adoption, and improve how stream processing infrastructure is used end-to-end
• Define and implement operational best practices (e.g., shuffle sharding, cellular architecture, load shedding, automated state recovery) to improve resilience and reliability at scale
• Drive fleet-level automation and standardization ("pets" to "cattle") through self-service workflows, safer rollouts, and self-healing systems that reduce manual operations
• Lead initiatives that raise the bar on Flink availability and state durability (e.g., multi-region strategies, disaster recovery readiness, operational readiness reviews, incident learning)
• Evaluate and productionize Flink ecosystem capabilities (e.g., SQL, connectors, state backends) to improve developer experience and scalability without compromising reliability
• Work closely with the open source community to identify opportunities for adopting new open source features as well as contribute back to OSS

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• This is a Staff-level role - that typically means 10+ years of experience building, operating, and evolving large-scale production systems
• Experience as a technical lead for team(s) working on distributed systems, including scaling them in fast-moving environments
• Hands-on experience with big data technologies such as Flink, Spark, Kafka, Pulsar, or Pinot
• Experience developing, maintaining and debugging distributed systems built with open source tools
• Experience building and scaling infrastructure as a product
• Strong software engineering skills and a passion for Big Data Distributed Systems
• Ability to write high quality code (in programming languages like Go, Java, Scala, etc)
• Comfortable operating with high autonomy and ownership
• Growth mindset and a willingness to learn quickly, explore ambiguous problem spaces, and dive deep when needed
• Strong written and verbal communication skills, including the ability to produce clear technical documentation

Preferred qualifications

• Experience operating streaming infrastructure as a platform (e.g., Flink clusters, Kafka, Pulsar) for internal customers at scale
• Deep hands-on experience authoring, optimizing, and operating real-time processing frameworks such as Flink, Spark Streaming, Storm, or Kafka Streams in production
• Experience building or operating control planes for managing large-scale infrastructure
• Open source contributions to data processing or big data systems (Hadoop, Spark, Celeborn, Flink, etc)

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

Canada: the pay range for this role is $216,000 to $297,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.

This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.

What You'll Do

• Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
• Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
• Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
• Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
• Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability 
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have a strong interest in LLM serving; prior inference or ML experience is not required 
• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With:

• LLM inference optimization, batching, and caching strategies
• Capacity-constrained scheduling or shared-resource test infrastructure
• Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
• Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
• Proficiency in Python or Rust

About the role

We are seeking a Staff Software Engineer to build and operate the safety, oversight, and intervention mechanisms that protect Claude on third-party cloud service provider (CSP) platforms. As the engineer responsible for Safeguards on those surfaces, you will ensure that every request served through our CSP partners is monitored for misuse, enforced against policy, and compliant with the data residency and privacy commitments that enterprise CSP customers expect.

You will sit at the seam between the Safeguards organization and the Cloud Inference team: taking classifiers, detection signals, and enforcement policies developed by Safeguards and making them run reliably inside a CSP partner’s infrastructure at serving-path latency and scale. You will own the architecture that lets our safeguards operate within those constraints without gaps. You will build, deploy and operate the multi-layered defenses that catch unwanted model behavior in real time, the telemetry pipelines that give us situational awareness over CSP traffic, and the enforcement hooks that let us act quickly when something goes wrong. Your work will directly determine whether Anthropic can ship frontier models on CSP platforms at the same safety bar we hold ourselves to on our first-party API.

Responsibilities:

• Build, deploy and operate real-time safeguards infrastructure—classifiers, rate limits, enforcement actions, and intervention hooks—embedded directly in the third-party CSP inference serving path
• Design and maintain the data residency and privacy architecture for safeguards signals on CSP platforms, ensuring we can detect abuse and monitor model behavior while honoring regionalization boundaries and enterprise contractual commitments
• Develop telemetry, logging, and evaluation pipelines that give Safeguards, Policy, and T&S operational teams situational awareness over CSP traffic and close the visibility gap between third-party and first-party serving
• Dive into the CSP serving stack to identify the lowest-impact points to gather signals or introduce interventions without degrading latency, stability, or overall architecture
• Hold a high operational bar: own on-call, drive root-cause analyses and postmortems for safeguards incidents on CSP platforms, and build systems that reduce the human intervention required to keep Claude safe
• Work closely with Safeguards research, Policy & Enforcement, the Cloud Inference team, and CSP partner contacts to turn detection research and policy decisions into production enforcement that works inside a partner’s cloud.

You may be a good fit if you:

• Have a Bachelor’s degree in Computer Science, Software Engineering, or comparable experience
• Have 7+ years of experience in high-scale, high-reliability software development, ideally with exposure to trust & safety, anti-abuse, fraud, or integrity systems
• Are proficient in Python and comfortable working across the stack—from request-path services to data pipelines to internal tooling
• Think adversarially: you can see a system from a bad actor’s perspective, anticipate how they will respond to countermeasures, and design defenses in depth rather than single points of enforcement
• Have experience scaling infrastructure to accommodate rapid traffic growth while keeping latency and reliability within tight budgets
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Have strong communication skills and can explain complex technical and risk tradeoffs to non-technical stakeholders across Policy, Legal, and partner organizations
• Enjoy working in a fast-paced, early environment; comfortable with adapting priorities as driven by the rapidly evolving AI space

Strong candidates may also have experience with:

• Building trust and safety, anti-spam, fraud, or abuse detection and mitigation mechanisms for AI/ML systems, or the infrastructure to support these systems at scale
• Machine learning serving infrastructure (GPUs/TPUs, inference servers, load balancing) and the operational realities of running models in production
• Major cloud platform internals—IAM, Network/service perimeter controls, regional resource constraints, cloud-native logging/monitoring—or experience shipping software that runs inside a partner’s cloud rather than your own
• Data residency, privacy engineering, or compliance-constrained architectures, particularly where telemetry has to stay within regional or contractual boundaries
• Working closely with operational and human-review teams to build custom internal tooling, admin UX, and alerting
• Adversarial mindset: has shipped defenses against motivated attackers before, knows what it feels like when they adapt, and can sprint to close a gap before it becomes an incident
• Comfortable operating at the intersection of platform/infra engineering and trust & safety—neither a pure infra engineer nor a pure T&S engineer, but someone who can credibly do both
• Has shipped software that runs inside someone else’s infrastructure (partner cloud, embedded deployment, or similar) and knows how to get things done when you don’t control the whole stack
• Senior enough to own a cross-team seam independently, drive consensus across orgs, and make latency/safety tradeoff calls without escalation
• TypeScript or Rust, and agentic coding tools such as Claude Code

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We're searching for a Staff Security Platform Engineer to join our Enterprise Security Engineering team, reporting to the Technical Lead Manager of Security Engineering.

Aurora is scaling its autonomous trucking operations, and we need someone who makes our security tools actually work, not just deployed, but deeply configured, continuously tuned, and fully leveraged. This role is for the practitioner who has spent their career living inside security platforms: the person who knows their EDR better than the vendor's own support team, who can write a SIEM query from memory, and who instinctively knows when an alert is misfiring and exactly why.

This is not a software engineering role. It's a role for an elite security operator — someone with the instincts of a seasoned SOC analyst and the technical depth to own the platforms that power detection, response, and protection at enterprise scale. If you find deep satisfaction in mastering a tool, closing a coverage gap, or hunting down a threat that nobody else noticed, this role was written for you.

In this role you will

• Own the operational health, configuration, and continuous improvement of Aurora's enterprise security platform stack — including EDR/XDR, MDM, SIEM, DLP, IAM/IGA, DNS security, Email security, and PKI — ensuring each tool is tuned, policy-complete, and delivering reliable signal.
• Develop and refine detection rules, correlation logic, and alert policies, reducing noise while ensuring Aurora maintains high-fidelity coverage against real threats.
• Conduct proactive threat hunting across Aurora's security telemetry — forming hypotheses, querying logs, and investigating anomalies before they surface as incidents.
• Serve as the deepest internal expert on Aurora's enterprise security tooling, acting as the escalation point for complex platform issues, misconfigurations, and detection failures.
• Participate in the team's on-call rotation, leading deep-dive investigations into security alerts and incidents and driving triage, containment, and root cause analysis.
• Continuously audit and validate that existing security controls are configured to actually do what they're supposed to do — not just deployed and forgotten.
• Maintain operational runbooks, detection documentation, and platform configuration records, ensuring the team can operate consistently and scale institutional knowledge.

Required qualifications

• 12+ years of hands-on experience in enterprise security operations, security platform administration, or a senior SOC engineering role — with a career built on deep operational ownership of security tooling rather than software development.
• Expert-level proficiency administering and operating at least two enterprise security platforms (e.g., CrowdStrike, SentinelOne, Splunk, Panther, Sentinel, Jamf, Kandji/Iru, Puppet, WorkspaceONE, Intune, Zscaler, Okta, Proofpoint, Wiz, osquery), with strong working knowledge across several others.
• Demonstrated ability to tune and optimize security platforms beyond out-of-the-box configurations — writing custom detection logic, adjusting policy sets, and validating control effectiveness.
• Strong log analysis and threat hunting skills: you know how to build a hypothesis, write the query, follow the thread, and know when to escalate.
• Experience conducting thorough incident investigations — triage, containment, root cause analysis, and post-incident review — and communicating findings clearly to technical and non-technical stakeholders.
• Ability to assess security control effectiveness: not just "is this tool deployed" but "is it configured correctly, covering the right scope, and generating actionable signal."
• Comfort working under pressure in ambiguous, fast-moving situations with competing priorities.

Desirable qualifications

• Scripting ability for automation, log parsing, or workflow improvement (Python, Bash, or similar) — you don't need to be a software engineer, but you can write a script when it saves you an hour.
• Deep familiarity with MITRE ATT&CK as an operational tool for detection gap analysis and threat hunting hypothesis development.
• Experience with AWS security telemetry (CloudTrail, GuardDuty, Security Hub) and integrating cloud signals into a corporate SIEM.
• Familiarity with Zero Trust and identity-centric security models as they apply to policy enforcement in IAM and endpoint platforms.
• Platform-specific certifications such as CrowdStrike Certified Falcon Administrator, Splunk Core Certified Power User, or equivalent — or practitioner certifications like GCIH, GCIA, GCFE, or GCFA.

The base salary range for this position is $189,000 - $274,000 per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

Join Airtable as a Product Security Engineer and play a pivotal role in shaping the security of our rapidly evolving platform as we expand our AI and LLM-powered offerings. You will join the team responsible for safeguarding the application layer of Airtable’s platform.

You will partner closely with product engineering teams to build paved roads, frameworks, and automated controls that make the secure path the easy path for our engineering teams. You will help influence application security at scale, ensuring our products are secure by design.

What you'll do

• Develop self-service security frameworks and "paved roads" that allow engineering teams to ship secure code by default.
• Focus on automated guardrails for common vulnerabilities, while prioritizing deep-dive design reviews into complex business logic and data isolation issues (for example, multi-tenant isolation and authorization/permission bypasses) that automated tools cannot catch.
• Partner with product and engineering teams to review designs early, contribute to threat modeling for new features and complex initiatives, and provide clear, actionable security guidance.
• Research emerging threats and evolving best practices, specifically regarding AI and LLM safety, and implement controls to secure these workflows.
• Manage and evolve our approach to external penetration testing and bug bounties, driving remediation for findings and treating vulnerability management as an engineering problem.
• Contribute to the long-term roadmaps, metrics, and strategic planning for the security team.
• (Senior/Staff L5+) Lead complex threat modeling sessions for major product launches and define secure coding standards, and actively mentor other engineers to raise the technical security bar across the organization.

Who you are

• 4+ years of experience in product security or application security, with experience shipping production code. Please note this is not an early career position.
• You have a strong background in computer science or a related field, with proficiency in writing clean, maintainable code.
• You have deep familiarity with JavaScript or TypeScript, Node.js, and modern web application frameworks, and can reason about the security implications of systems built on them.
• You have hands-on experience securing LLM integrations and identifying prompt injection or data leakage risks.
• You are proficient in writing and reviewing code and treat security as an engineering problem to be solved with software, not just policies.
• You excel at communicating complex security risks to non-security stakeholders and enjoy collaborating cross-functionally to find solutions that balance security with engineering velocity.
• You are comfortable working in a fast-paced environment, navigating ambiguity, continuously learning about emerging threats and technologies, and contributing to long-term security strategy.

Airtable is an equal opportunity employer. We embrace diversity and strive to create a workplace where everyone has an equal opportunity to thrive. We welcome people of different backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or any characteristic protected by applicable federal and state laws, regulations and ordinances. Learn more about your EEO rights as an applicant. 

VEVRAA-Federal Contractor

If you have a medical condition, disability, or religious belief/practice which inhibits your ability to participate in any part of the application or interview process, please complete our Accommodations Request Form and let us know how we may assist you. Airtable is committed to participating in the interactive process and providing reasonable accommodations to qualified applicants.

#LI-remote

We are seeking a visionary and technically strong Staff Materials Engineer to lead the development and advancement of material technologies that are core to the Oura product experience. This role will focus on driving innovation and execution across metal surface treatments, PVD/CVD, platings and other novel inorganic coating materials - ensuring performance, reliability, and premium user experience across current and future hardware platforms.

What You’ll Do:

• Manage a roadmap for materials engineering across metal surface treatments, PVD/CVD, platings and emerging technologies.
• Drive R&D and materials selection efforts for current and next-generation products, balancing form factor, performance, biocompatibility, manufacturability, and sustainability.
• Establish and optimize material and bonding processes for high-volume manufacturing.
• Partner with PD, ID, and Ops teams to understand needs and integrate materials solutions early in the product development lifecycle.
• Define standardized materials testing and coupons to characterize new and existing materials within the area of expertise.
• Work with external vendors and strategic partners to evaluate new materials and coatings, qualify processes, and ensure scalability and reliability.
• Define and oversee materials validation, characterization, and reliability testing methodologies.
• Collaborate closely with Reliability and Regulatory teams to ensure material compliance and performance in real-world use conditions.
• Identify and mitigate material risks across the product lifecycle, from prototype to production and field usage.

What We’re Looking For:

• Bachelor's degree in Materials Science, Chemical Engineering, Mechanical Engineering, or a related field. 
• 10+ years of experience in materials engineering of PVD/CVD and metal surface treatments
• Proven experience developing materials and processes for consumer electronics, medical devices, or wearables.
• Strong background in materials characterization, surface chemistry, and process development.
• Strong global connections and experience working with contract manufacturers and materials suppliers across Asia and globally.
  
  

Nice to Have:

• Advanced degree (MS/PhD) in Materials Science, Chemical Engineering, Mechanical Engineering, or a related field.
• Experience with biocompatibility and regulatory requirements for skin-contact products.
• Background in sustainability-focused material development.

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own plus employee discounts for friends & family
• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
• Paid sick leave and parental leave

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1: $198,050 - $267,950

Oura is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Oura are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics.

We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Disclaimer: Beware of fake job offers!
We’ve been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note:

• Our jobs are listed only on the ŌURA Careers page and trusted job boards.
• We will never ask for personal information like ID or payment for equipment upfront.
• Official offers are sent through Docusign after a verbal offer, not via text or email.

Stay cautious and protect your personal details.

About the Role:

We're looking for a Senior Staff Security Engineer to lead Gusto's edge and network security strategy, owning the design and operation of our Cloudflare WAF, DDoS protection, Zero Trust, and broader perimeter controls. The ideal candidate brings deep, hands-on Cloudflare expertise and a proven track record of hardening edge and network architectures at scale, including tuning WAF rulesets, defending through live DDoS events, and shipping Zero Trust rollouts engineers actually adopt. You think in terms of layered defense, measurable risk reduction, and automation over manual toil. In this role, you'll serve as a force multiplier across the security org, partnering with infrastructure and product teams to make high-impact architectural decisions that compound over time.

About the Team:

The Gusto's Enterprise Security Engineering team, a small but high-leverage group responsible for cloud security posture, edge and network defense, container security, secrets management, and endpoint protection across the company. The team runs a modern stack including Cloudflare, Wiz, CrowdStrike, Panther, and Tines, scaling impact through automation, IaC, and AI-augmented tooling. The work carries real stakes, protecting the payroll, benefits, and HR systems that hundreds of thousands of small businesses and their employees rely on every day. The team is engineering-first, with most of the roadmap living in code and a strong emphasis on partnering with infrastructure and product teams rather than gatekeeping them.

Here’s what you’ll do day-to-day:

• Design and operate Gusto's edge security stack including Cloudflare WAF, DDoS protection, Bot Management, WARP, Gateway, and Access, tuning rules against real traffic and shaping how engineers and operations teams reach internal systems securely.
• Own the network security perimeter across AWS and the edge: VPC design, Network Firewall, Shield, CloudFront, NACLs, and egress filtering, all codified in Terraform and Crossplane, observable, and consistently enforced.
• Develop policy-as-code patterns for WAF rules, network policies, and edge configuration so changes ship through pull requests with review, testing, and clean rollback paths.
• Build detections and alerting on edge and network telemetry including Cloudflare logs, VPC Flow Logs, and CloudTrail flowing into Panther, and lead incident response for perimeter and network events.
• Contribute broadly across the security engineering surface including cloud posture, container security, IAM, vulnerability management, and on-call, bringing a strong generalist instinct to wherever the work is most critical.
• Operate as an AI-native engineer, using Claude Code, MCP-driven tooling, and agentic workflows as a daily force multiplier across investigation, automation, and detection engineering.
• Prototype and ship agents, custom MCP servers, and LLM-assisted automations that compress security work from days to minutes and raise the bar for what one engineer can own.

Here’s what we're looking for:

• 10+ years of hands-on security engineering experience, with significant time owning edge, network, or perimeter security at scale.
• Deep, production-grade expertise with Cloudflare's security stack including WAF, DDoS, Bot Management, WARP, Gateway, and Access, covering rule tuning, incident response, and Zero Trust rollouts.
• Strong network architecture skills across edge and cloud: TLS/mTLS, segmentation, egress controls, DDoS resilience, and AWS networking including VPC, Network Firewall, Shield, CloudFront, and NACLs.
• Fluency with policy-as-code, Terraform, and CI/CD-first delivery of security controls; Crossplane or similar a plus.
• Solid generalist foundation across cloud security, IAM, container security, and detection engineering, with hands-on incident response experience on edge and network telemetry in a modern SIEM.
• AI-native working style with daily use of Claude Code or equivalent agentic tooling, and a track record of building AI-assisted workflows including custom MCP servers, agents, and LLM automations that compound team output.
• Excellent written and verbal communication; you can take a complex perimeter decision and explain the tradeoffs to a staff engineer, a PM, and a VP without changing the substance.
• Relevant certifications a plus including AWS Certified Advanced Networking Specialty, AWS Certified Security Specialty, Cloudflare Certified Security Associate/Professional, CKS, or equivalent.

About Hightouch

Hightouch is the modern AI platform for marketing and growth teams. Our AI agents reimagine marketing workflows, allowing marketers to create content, plan campaigns, and execute strategies with transformational velocity and performance.

Hightouch is a rare company built on the intersection of two fundamental technological shifts: advances in LLMs and agentic AI, and the creation and rapid adoption of cloud data warehouses like Snowflake and Databricks. Building on these tailwinds, we’ve become a leader in AI marketing and partner with industry leaders like Domino’s, Chime, Spotify, Ramp, Whoop, Grammarly, and over 1000 others.

Our team focuses on making a meaningful impact for our customers. We approach challenges with first-principles thinking, move quickly and efficiently, and treat each other with compassion and kindness. We look for team members who are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals.

About the Role

We are looking for a Staff AI Productivity Engineer to accelerate how our engineering organization works with AI coding tools. This is a hands-on technical role focused on building infrastructure, tooling, and documentation that makes AI agents dramatically more effective across our codebase.

AI tools are evolving rapidly, and we believe the companies that invest in making agents truly productive - not just available - will have a significant advantage. You'll own this problem end-to-end: from setting up cloud development environments where agents can run autonomously, to building MCP integrations that give agents access to our internal systems, to creating the documentation and context that helps agents understand how we build software.

You’ll have the hands-on acumen to do a lot of the heavy lifting yourself and the leadership skills to drive cross-team efforts to raise the bar everywhere. This role is a companion role to our Developer Productivity role but has a distinct focus: while Dev Productivity owns the build/test/deploy pipeline, you'll own the AI-assisted development experience. An exceptional candidate could wear both hats.

Some of the problems we’ll be working on include:

• Own the agentic development environment: Ensure agents can operate in independent cloud-based development environments, execute our full test suites, examine build results visually, etc
• Build our tooling integrations: Build MCP server integrations that connect our agents to the systems needed to build and debug software, such as CircleCI, Slack, Datadog, Github, etc
• Documentation and context: Own our repo-wide agents.md file and work with teams to ensure our library of agent guidance and skills is continually pushing the bar. Ensure our conventions and package structures are exposed in ways that agents can effectively use
• Enablement: Work with our engineers to understand where agents are struggling and address root causes such as better docs, tooling access, etc. Develop tooling for non-engineers to make simple visual updates to our application
• Serve as a “PM” for internal AI agents: Consistently keep us on the leading edge of AI productivity trends by staying abreast of what is state-of-the-art in industry and driving those improvements across Hightouch

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000 - $320,000 USD per year, which is location independent in accordance with our remote-first policy. We also offer meaningful equity compensation in the form of ISO options, and offer early exercise and a 10 year post-termination exercise window.

About You

You are an engineer with a passion for solving hard technical problems that generate real value for customers. You’re motivated by high ownership and are comfortable in a fast-paced, startup environment.

Must have

• Strong software engineering fundamentals—you can dive into complex backend code and understand it quickly
• Deep hands-on experience with AI coding agents (Claude Code, Cursor, Copilot, Devin, or similar)
• Experience writing effective agent documentation, custom instructions, or context files that meaningfully improved agent output
• Track record of building developer tools or infrastructure that other engineers actually use
• Comfortable working across the stack: you'll touch CI/CD, cloud infrastructure, internal tooling, and application code

Nice to have

• Experience building or contributing to MCP servers or similar agent-tooling integrations
• Background in developer productivity, platform engineering, or developer experience roles
• Experience with our stack: TypeScript/JavaScript monorepos, Go, GraphQL
• You've set up sandboxed or containerized development environments at scale

Interview Process

Our goal with the interview process is to balance speed with giving both parties opportunities to assess whether there is a strong mutual fit. We will ask you questions, but we want you to ask us questions! Our technical interviews focus on how you design systems because we believe this is the best way for us to see how you work and for you to see how we collaborate. We don’t ask you to write code to solve technical brainteasers that don’t appear in your day to day job.

• Apply: Curl jobapi.hightouchdata.com on port 13784 and have followed those instructions before applying. It'll only take a minute!
• Recruiter Screen [30m]: Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit
• System Design Screen [45m]: Designing a data processing feature end-to-end
• AI Skills Interview [60m]: We’ll dive into how you leverage AI and how you’ve helped others do the same
• Hiring Manager Interview [45m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles
• System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical

We are looking for a Staff Forward Deployed Engineer who is passionate about solving complex cloud infrastructure challenges in the fast-growing AI/ML space. This is a high-impact position designed to be the "technical tip of the spear" for our most strategic AI-Native (ANE) customers.

As an FDE, you will sit at the intersection of Product Engineering and Customer Implementation. You will be embedded directly with our most strategic customers to drive transformational AI adoption. You will collaborate closely with customer teams to ship advanced AI applications that solve real world business problems.

You will build the tools, migration scripts, and AI starter kits that don't just solve one customer's problem, but scale the entire DigitalOcean AI Cloud ecosystem. Your mission is to accelerate "time-to-inference" in production at scale and serve as a critical feedback loop, ensuring our product roadmap is informed by the world's most demanding AI workloads.

What you’ll do:

• Embedded Customer Engineering: Partner deeply with strategic ANEs to manage complex migrations, build production-ready PoCs, and execute hands-on application builds on our GPU infrastructure.
• Build Scalable Assets & Tooling: Operationalize field learning by building migration planners, reusable systems, benchmarking frameworks, model optimization agents, and deployment automation scripts (e.g., Terraform/Pulumi) that standardize how AI workloads are deployed and tuned across DigitalOcean.
• Develop AI "Starter Kits": Create pre-built GenAI agents, solution templates, and notebooks (e.g., LangGraph, CrewAI) tailored to popular and advanced business needs.
• Drive the Product Roadmap: Act as the frontline technical voice for CPTO, surfacing architectural gaps and edge cases to inform core product development. Transition field-built tools into native product features.
• New Tech Validation: Lead the early testing and integration of emerging AI frameworks to ensure a first-class developer experience on DigitalOcean.
• Partner & GTM Enablement: Co-develop delivery frameworks with Strategic and Technical partners to enable repeatable, high-quality deployments at scale.
• Market Leadership: Produce field-tested demo kits and deployment guides that support new product releases with practical, validated assets.

Key Metrics

• Customer Adoption: Number of high-impact production workloads landed; reduction in average "time-to-production"; and Pilot-to-Production conversion rates.
• Asset & Tooling Delivery: Number of reusable tools (agents, scripts, playbooks) delivered per quarter and their subsequent adoption rate by the crossfunctional teams and customers.
• Field Enablement & Scale: Measured by the successful handoff and execution of FDE-defined deployment patterns to technical partners and the internal adoption rate of FDE playbooks across all customer-facing technical teams.
• Product Influence: Number of roadmap features or architectural changes directly attributed to FDE feedback and validated customer hypotheses.

What You’ll Add to DigitalOcean:

• AI/ML Architecture & Domain Expertise: Significant experience in the AI/ML lifecycle, specifically hosting large language or multimodal models using inference engines like vLLM, SGLang, or Modular. You have a deep understanding of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
• Distributed Systems & Infrastructure Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton). Expert proficiency in Kubernetes (K8s) and the design of distributed systems, including microservices, messaging systems, databases, and Infrastructure as Code. You can seamlessly integrate AI workloads with core cloud services (Networking, VPC, Storage, Compute).
• High-Performance Inference & Hardware Optimization: Hands-on experience with distributed inference serving frameworks (e.g., llm-d, NVIDIA Dynamo, or Ray Serve). You understand GPU-level optimization and have experience with interconnect technologies like NVlink, XGMI, or RoCE to maximize hardware efficiency.
• Software Engineering Foundation: Strong production coding skills in Python or Go with the ability to build high-quality tools, automation, and internal assets.
• Data-Driven Performance Insight: Proven ability to benchmark AI infrastructure and perform GPU utilization tuning to optimize customer ROI and workload performance.
• Consultative Execution: Proven ability to establish instant technical credibility with CTOs and Lead Architects while managing high-stakes technical migrations.

Preferred

• Experience with emerging AI orchestration frameworks like LangGraph, CrewAI, or LlamaIndex.
• A background in technical consulting or "Forward Deployed" roles at high-growth AI or infrastructure companies.
• Experience building and scaling "Center of Excellence" models or partner delivery frameworks.
• Active contributor to open-source AI projects or technical communities.

Compensation Range: 

• $195,000 - $239,000

*This is a remote role

JR: 2026-7748

#LI-Remote

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We're searching for a Staff Security Engineer to join our Enterprise Security Engineering team, reporting to the Technical Lead Manager of Security Engineering.

Aurora is scaling its autonomous trucking operations, and the security foundations protecting our employees, devices, internal systems, and data need to scale with us. We're looking for a deeply technical enterprise security engineer who is as comfortable in a code editor as in a security console — you build the systems that make Aurora's security operations possible. This is a role for someone who can architect robust enterprise security solutions, write the code to implement them, and partner across Engineering and IT to make sure security is embedded from the start, not bolted on at the end.

This is not a security operations-only role. It sits squarely in enterprise security engineering, where the work is designing, building, and owning the platforms, integrations, and automation that power Aurora's internal security posture at scale.

In this role you will

• Own the architecture and implementation of Aurora's enterprise security controls — designing the systems and integrations that protect Aurora's endpoints, identities, internal infrastructure, and SaaS environment.
• Design and build Aurora's security telemetry and detection infrastructure, including log pipelines, SIEM integrations, and alerting frameworks — in partnership with the Security Operations Engineer who owns ongoing tuning and rule development.
• Define and enforce enterprise security standards, conducting architecture and design reviews to ensure alignment with Aurora's security posture and risk tolerance.
• Partner with IT, Infrastructure, and Engineering teams to embed security requirements early — shifting left on corporate IT initiatives before they become technical debt.
• Build automation and tooling that extends the capabilities of Aurora's security platforms, reduces manual operational burden, and scales the team's impact.
• Serve as the escalation point for enterprise security incidents requiring engineering-level investigation or remediation, and participate in the team's on-call rotation.
• Translate security strategy into concrete, executable engineering projects with clear milestones and measurable outcomes.

Required qualifications

• 12+ years of hands-on experience in enterprise security engineering or corporate information security — specifically securing employee-facing systems, endpoints, identities, and internal infrastructure (not product or application security).
• Proficiency in at least one programming language, used in a security context — writing production-quality automation, integrations, or internal tooling (the team primarily uses Go; Python is also common).
• Experience architecting and integrating enterprise security platforms — designing API integrations, automating workflows, and building tooling that extends platform capabilities across domains such as EDR/XDR, MDM, IAM/IGA, DLP, SaaS security, cloud security, or PKI.
• Experience designing and building security telemetry pipelines and detection infrastructure — log ingestion, normalization, SIEM integration, and alerting architecture.
• Experience leading cross-functional security engineering projects — defining scope, driving execution, and aligning stakeholders across Engineering and IT.
• Track record of conducting security architecture reviews and translating findings into actionable, risk-prioritized remediation plans.
• Experience evaluating security posture and identifying systemic gaps, with a bias toward building durable solutions rather than one-off fixes.

Desirable qualifications

• Experience with Zero Trust architecture and identity-centric security models (BeyondCorp-style or similar).
• Familiarity with NIST CSF, MITRE ATT&CK, and CIS Benchmarks as engineering inputs — used to inform what to build and how to validate it, not just as compliance checkboxes.
• Hands-on AWS security experience (SCPs, GuardDuty, Security Hub, IAM, etc.) and familiarity with integrating cloud security signals into a corporate security platform.
• Experience with applied cryptography and PKI in a production enterprise environment — certificate lifecycle management, CA design, or secrets management.
• Familiarity with securing AI/ML platforms or applications built on LLMs, RAG pipelines, or MCP-based architectures.
• Security certifications such as CISSP, GCED, GREM, or similar (valued but not required).

The base salary range for this position is $189,000 - $274,000 per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#Mid-Senior 

• Help design, train, with a focus towards deploying onboard machine learning models that improve the performance/latency of the Kodiak autonomy stack which includes quantization, pruning, converting to ONNX/TensorRT, custom GPU kernels and profiling.
• Help identify and achieve parity between onboard and deployed offboard models using validation on HIL 
• Collaborate with cross-functional teams including perception, planning, simulation, and autonomy infrastructure to integrate ML models into production systems.
• Analyze real-world driving logs to identify edge cases and improve model robustness and safety.
• Use profiling tooling to additionally help improve the train time for models by identifying and removing bottlenecks.
• Contribute to the development of scalable AI infrastructure that supports continuous learning and deployment across Kodiak’s fleet.

• MS or PhD in Computer Science, Robotics, Machine Learning, or a related technical field, or equivalent practical experience.
• 6+ years experience deploying machine learning or deep learning systems in production environments.
• Proficiency in Python, C++ and modern ML frameworks such as PyTorch or TensorFlow.
• Experience working with large-scale distributed training systems.
• Solid understanding of optimization, and machine learning fundamentals.
• Strong software engineering fundamentals including testing, debugging, and system design.
• Ability to work collaboratively across teams to solve complex autonomy and robotics challenges.

What we offer:

• Competitive compensation package including equity and annual bonuses
• Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and  MetLife (including a medical plan with infertility benefits)
• MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
• Flexible PTO, 10 paid holidays, and generous parental leave policies
• Our office is centrally located in Mountain View, CA
• Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging
• Long Term Disability, Short Term Disability, Life Insurance
• Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation) 
• Fidelity 401(k)
• Commuter, FSA, Dependent Care FSA, HSA
• Various incentive programs (referral bonuses, patent bonuses, etc.)

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

San Francisco: the pay range for this role is $246,500 to $339,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About the role

Anthropic is building Treasury with scale and automation in mind from the start. We're creating modern, well-controlled processes that can grow with the business; supported by strong systems, clear governance, and practical use of AI-enabled tools. We're designing touchless, AI-native workflows from day one, with SOX-grade controls built in rather than bolted on.

This role reports to the Treasury Ops Lead and plays a central part in building and running the company's Treasury Operations foundation. You'll manage core activities: daily cash positioning, global bank account administration, intercompany funding, payment controls, and Treasury reporting - while improving processes so the function scales efficiently as the company grows.

This is a hands-on role for someone who enjoys both execution and process building. You should be comfortable running key day-to-day activities while identifying opportunities to improve, automate, and strengthen controls.

You'll be the second person in a Treasury Ops function at a company that's growing fast and building deliberately. The processes you design in your first six months are the ones the company runs on at 10x scale. The ownership is end-to-end, and the toolkit is ours - you'll design Treasury workflows that are AI-native from the first draft, the way only Anthropic can.

What you'll do:

Core Treasury Operations

• Manage daily cash positioning across entities and currencies, including tracking balances and consolidating cash activity

• Lead global bank account management; account opening and closing coordination, signer updates, KYC documentation, and portal administration

• Help design and manage intercompany settlement and funding processes, including documentation and ongoing improvement

• Maintain short-term cash forecasting, including variance tracking and reporting

• Support payment workflows and controls; approval routing, exception handling, operational process improvements

• Support Letter of Credit and Bank Guarantee issuance and post-M&A Treasury integration activities

Systems & Automation

• Support TMS implementation, bank connectivity, reporting enhancements, and process standardization

• Design the "Claudification" layer: identify which workflows go touchless, build the automation, keep humans in the decisions that need judgment

• Partner with Finance Systems to simplify and automate Treasury processes

• Own Treasury data quality - the source of truth that everything downstream depends on

Controls & Governance

• Execute Treasury processes with strong focus on controls, documentation, segregation of duties, and audit readiness

• Support development and maintenance of Treasury policies, procedures, and control documentation

• Document Treasury controls for SOX readiness; not as a separate project, but as how the work gets done

• Partner with Accounting on close activities, reporting, and audit requests

What we're looking for:

• 5–8 years in Treasury operations, ideally at a growth-stage or scaling company where you saw processes get built, not just inherited

• You currently own the daily cash position. You log into the bank portals, you run the position, you execute the wires. This is a doing role, not a managing role

• Treasury-native depth. You came up through Treasury; TMS, KYC mechanics, bank account administration, cash positioning judgment. This isn't a payments-processing seat; it's a Treasury seat

• Player-coach DNA. You still do the work; run the cash position, chase the KYC doc, troubleshoot the wire - while building the system so nobody has to do it manually next quarter

• Hands-on TMS experience. You've worked in a Treasury Management System (Kyriba, GTreasury, Trovata, Quantum, or similar): configured it, broken it, fixed it. Implementation experience is a plus but not required

• SOX in your DNA. You think in audit trails, approval chains, and segregation of duties; not because compliance makes you, but because well-controlled processes are the ones that scale

• Comfort with ambiguity. There's no playbook here. You'll write it

• AI-first mindset. Not a prompt engineer; a Treasury person who wants the model handling data so you can focus on decisions.

Strong candidates may also have:

• Exposure to SOX readiness or IPO prep, even as a contributor

• Multi-entity, multi-currency operations background

• Worked with bank APIs or Treasury aggregators (Trovata, Kyriba, or direct connectivity)

• APAC or EMEA bank account opening experience

The Role

We are seeking a Senior Staff Engineer to join our team. SoFi is building out a new team to develop crypto products and services for our members.  Recent developments made a path for SoFi to begin to re-enter the space and expand on our product offerings with intuitive, secure and fully featured products across crypto Investing, Transfers, Payments, Custody and beyond.  

On our team, you will be in the middle of it all – implementing functionality, architecting our system, squashing bugs, maintaining the health of our code, and continually growing as an engineer. The ideal candidate is both forward-thinking and hands-on, has a strong sense of ownership and drive for delivery, and is a good mentor and co-worker. At SoFi, we pride ourselves on the collaboration between Product, Design and Engineering and so you will be involved in the entire product lifecycle, from ideation through building, deploying and continual improvement and evolution.

At SoFi, you’ll become part of a new kind of finance company whose ambition is to help our members achieve financial independence and reach their goals. We aim to be at the center of our members’ financial lives, and to help every member get their money right. We created student loan refinancing, addressing the biggest financial challenge of a new generation through a modern approach to lending and personal finance. Next we expanded our products and services across loans, wealth management, and insurance. SoFi has achieved significant growth, with ambitious plans ahead, but to continue this growth we need great talent. And that starts with you.

Key responsibilities

• Write production-grade, scalable backend code using Java, Kotlin, Spring Boot, and modern frameworks.
• Debug and resolve complex systems issues in high-scale, real-time services.
• Build high-quality, scalable systems with a focus on performance, security, and reliability in crypto products.
• Shape the technical architecture across SoFi’s crypto stack — wallets, custody, trading, and beyond.
• Drive new ideas and technical strategies that push our crypto offerings forward.
• Raise the bar on engineering through code quality, mentorship, and setting strong technical standards.
• Apply deep knowledge of crypto protocols, smart contracts, and blockchain infrastructure.
• Collaborate across teams to deliver reusable crypto services and integrate with SoFi’s broader platform.
• Mentor engineers and contribute to a culture of technical growth and curiosity.
• Lead discussions, reviews, and decisions across teams and with senior technical leadership.
• Make smart, pragmatic decisions that balance speed and quality.
• Stay curious — constantly learning new tools, protocols, and patterns in the evolving crypto space.
• Ask hard questions, give and take feedback well, and thrive in a collaborative, fast-moving environment.

What you'll need

• 8+ years programming experience, with significant experience in modern day languages and familiarity with AI tools.
• Expert understanding and hands-on experience building and operating large-scale fault-tolerant distributed systems, workflows, databases and mobile/web applications
• Expertise with Java / Spring / Kotlin / PostgreSQL / AWS. Expertise with any modern Java frameworks, REST APIs, and relational databases
• Deep understanding of code release, deployment orchestration / rollout mechanisms, logging, instrumentation, monitoring, and alerting in a microservices environment.
• Experience with public cloud infrastructure
• Excellent verbal and written communication skills and working with stakeholders across disciplines
• Understanding of blockchain fundamentals and distributed ledger technologies
• Familiarity with digital assets across major chains (Bitcoin, Etherium, …)
• Hands-on experience with smart contracts is a plus
• Familiarity with custody, settlement, and clearing of crypto transactions
• Experience with security and best practices for wallet management
• Exposure to crypto trading platforms, market data, and DeFi protocols
• Experience integrating with or building services using crypto infrastructure providers (e.g., Fireblocks, Zero Hash, Anchorage)
• Awareness of Web3 trends, including NFTs, DAOs, and Layer 2 solutions
• Prior work in or collaboration with crypto-native companies or fintechs
• Enthusiasm for the evolving digital asset ecosystem and its potential impact on financial services

Available Locations: San Francisco, CA

About the Role

Cloudflare’s Senior Forward Deployed Engineers (FDEs) operate at the intersection of product engineering and customer impact.

As an FDE, you will be embedded within one of Cloudflare’s most strategic global customers, working side-by-side with their engineering teams to build and deploy solutions using Cloudflare’s platform. Unlike traditional Solutions Architects or consultants, you will write production code, shape technical architecture, and directly influence how Cloudflare products are used at massive scale.

You will operate as a technical extension of both organizations - helping the customer ship faster while surfacing real-world product insights back to Cloudflare engineering.

This role is ideal for engineers who want to:

• Stay deeply technical
• Work on real production systems
• Influence product direction
• Build long-term partnerships with world-class engineering teams

Responsibilities

• Deep Technical Embedding: Serve as the dedicated, long-term technical partner within a strategic customer’s engineering organization, operating as a trusted extension of their team.
• Production-Level Engineering: Design, build, and deploy production-ready code and configurations directly into customer infrastructure using the Cloudflare platform.
• Technical Accountability: Own the account's technical success across the entire Cloudflare portfolio. Serve as the primary technical point of contact, with other Cloudflare technical resources taking direction from your technical strategy for the account.
• Operational Integration: Participate in customer engineering rituals, including daily standups, design reviews, and real-time incident response.
• Platform Advocacy & Adoption: Identify opportunities to accelerate the adoption of Cloudflare services, unlocking new capabilities across the customer’s tech stack.
• Platform Breadth & Depth: Deep technical competence in building production applications on a modern stack, combined with the willingness and ability to go deep on all Cloudflare product areas. From Workers to security, networking, and observability.
• Feedback Loop & Product Influence: Surface real-world edge cases and product gaps directly to Cloudflare’s Product and Engineering teams to influence the developer platform roadmap.
• Strategic Relationship Management: Establish and maintain trusted technical relationships with senior leadership (Staff+ engineers, Directors, and VPs).
• On-Site Presence: Maintain a regular on-site presence at customer locations to foster deep collaboration and cultural alignment.

Requirements

• Proven Engineering Pedigree: 7+ years of professional software engineering experience. You are a builder at heart, with a track record of delivering production-grade systems, not just advising on them.
• Production Ownership & Operational Maturity: You have owned mission-critical services with real-world users. You understand the gravity of on-call rotations, the urgency of incident response, and the architectural rigor required to maintain "five nines" uptime.
• Active Practitioner: You are currently in the IDE. You have a "ship-first" mentality and maintain a high velocity, staying current with modern frameworks, languages, and deployment patterns.
• Full-Stack Architectural Depth: Broad technical fluency across the entire stack—from frontend performance and backend logic to database optimization and distributed infrastructure.
• AI-Native Development: You have integrated AI-augmented workflows (e.g., Windsurf, OpenCode) into your daily development cycle to accelerate prototyping and delivery.
• Systems Design & Strategic Thinking: Ability to decompose complex business requirements into scalable, resilient technical architectures. You can visualize the "big picture" without losing sight of the implementation details.
• Cloud Ecosystem Fluency: Deep experience with at least one major cloud provider (AWS, GCP, or Azure), including an understanding of serverless, networking, and security primitives.
• High Agency & Navigating Ambiguity: You are a self-starter who thrives in "zero-to-one" environments. You don't wait for a ticket; you identify the problem and own the solution from end-to-end.
• Executive Presence: Comfortable engaging in high-stakes technical and strategic discussions with VP-level stakeholders, with the ability to translate complex engineering trade-offs into business impact.

Nice to Have

• Direct experience building on Cloudflare Workers, or the broader Cloudflare Developer Platform.
• Previous experience at a fast-paced startup or in a customer-facing engineering role where you operated directly within a partner’s codebase.
• A visible public profile, including open-source contributions, technical blogging, or speaking engagements at industry conferences.

Compensation

Compensation may be adjusted depending on work location.

• For Bay Area based hires: Estimated annual salary of $194,000 - $266,000.

Equity

This role is eligible to participate in Cloudflare’s equity plan.

Benefits

Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

Health & Welfare Benefits

• Medical/Rx Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Accounts
• Commuter Spending Accounts
• Fertility & Family Forming Benefits
• On-demand mental health support and Employee Assistance Program
• Global Travel Medical Insurance

Financial Benefits

• Short and Long Term Disability Insurance
• Life & Accident Insurance
• 401(k) Retirement Savings Plan
• Employee Stock Participation Plan

Time Off

• Flexible paid time off covering vacation and sick leave
• Leave programs, including parental, pregnancy health, medical, and bereavement leave

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders.

You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency.

• Define technical strategy for agentic guardrails, explainability, and fleet orchestration.
• Ensure system reliability and performance across multiple security classifications and network types.
• Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance.
• Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members.
• Influence the long-term product strategy and technical roadmap for the Federal business unit.
• Consult on the architecture of AI-powered solutions for large-scale federal contracts.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. As a Staff Software Engineer, you will define and drive both the architectural roadmap and implementation of core platforms and software systems. You will be responsible for providing high-level vision and driving adoption across the engineering org for orchestration, data abstraction, data pipelines, identity & access management, and underlying cloud infrastructure.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

Impact and Responsibilities:

• Architectural Vision: You will drive the design and implementation of foundational systems, acting as a bridge between high-level business goals and technical goals.
• Cross-Functional Leadership: You will collaborate with cross-functional teams to define and drive adoption of the next generation of features for our AI data infrastructure.
• Technical Ownership: You are responsible for proactively identifying and driving opportunities for organizational growth, driving improvements in programming practices, and upgrading the tools that define our development lifecycle.
• Technical Mentorship: You will serve as a subject matter expert, presenting technical information to stakeholders and providing the guidance to elevate the engineering culture across the company.

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialities in back-end systems.
• Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
• Demonstrated a track record of independent ownership and leadership across successful multi-team engineering projects
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc.
• Experience with orchestration platforms, such as Temporal and AWS Step Functions.
• Experience with NoSQL document databases (MongoDB) and structured databases (Postgres).
• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, ArgoCD).

Nice to haves:

• Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt).
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

Staff Software Engineer, Full-Stack - Enterprise Gen AI

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a frontend-focused full-stack engineer to help build AI-powered applications that redefine enterprise workflows and push the boundaries of interactive AI. This role is ideal for someone who thrives in a fast-paced environment, enjoys working on a diverse set of projects, and has a passion for crafting high-quality, intuitive user experiences.

At Scale, you'll work on a mix of cutting-edge customer-facing AI applications and internal SaaS products. Our engineering team powers projects like TIME’s Person of the Year AI experience (see it in action), where our AI technology helped shape one of the most iconic features in media. You'll also contribute to Scale’s GenAI Platform (SGP), a powerful system that enables businesses to build and deploy AI agents at scale. Whether it’s developing interactive AI assistants, enterprise-grade web applications, or refining our core SaaS platform, you’ll play a crucial role in shaping how AI integrates into real-world applications.

You Will:

• Build and enhance user-facing AI applications for major enterprise customers, including high-profile media and Fortune 500 companies
• Develop and refine features for Scale’s GenAI Platform, empowering businesses to build, deploy, and manage AI-driven agents
• Design, build, and optimize polished, high-performance UIs using Next.js, React, TypeScript, and Tailwind
• Work closely with product managers, designers, and AI/ML teams to create seamless, intuitive, and impactful user experiences
• Integrate frontend applications with backend services, working with APIs, authentication systems, and cloud-based infrastructure
• Ship features at a rapid pace while maintaining a high level of code quality, performance, and accessibility

Ideally, You Have:

• 5+ years of experience developing frontend or fullstack applications in a modern tech stack
• Strong proficiency in Next.js, React, TypeScript, and Tailwind, with an eye for building polished, user-friendly interfaces
• Experience working on high-visibility, customer-facing applications and making trade-offs between speed and quality in fast-paced environments
• A passion for AI and experience working on interactive AI applications, agent-based systems, or data-rich web platforms
• Familiarity with backend technologies such as FastAPI, PostgreSQL, GraphQL, and cloud infrastructure like AWS, Azure, or GCP
• A track record of collaborating cross-functionally with design, product, and ML teams to bring AI-powered applications to life

This role is a unique opportunity to shape the future of AI-powered user experiences, working on projects that impact millions of users while developing tools that empower businesses to deploy AI at scale. If you’re excited by the intersection of AI, frontend engineering, and product design, we’d love to hear from you.

The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle is $248,400—$310,500 USD

. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.

You will:

• Own large new areas within our product
• Work across backend, frontend, and interacting with LLMs and ML models
• Deliver experiments at a high velocity and level of quality to engage our customers
• Work across the entire product lifecycle from conceptualization through production
• Be able, and willing, to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• Experience scaling products at hyper growth startups
• Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
• Proficient in Python or Javascript/Typescript, and SQL
• Experience with Kubernetes
• Experience with major cloud providers (AWS, Azure, GCP)

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

You will:

• Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
• Collaborate with cross-functional teams to define, design, and deliver new features.
• Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades.
• Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.
• Provide technical leadership, including: upholding and upleveling engineering standards across the organization, mentoring junior engineers. 

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems.
• Extensive experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.).
• Show a track record of mentoring and leading teams in successful projects.
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings.
• Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems.
• Experience driving cross functional collaboration and communication at an organizational or broader level. 

Nice to haves:

• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).
• Experience with performance tuning and cost optimizations of cloud based data platforms. 
• Experience defining a data lifecycle strategy and designing/implementing tooling for data privacy (i.e. GDPR) needs.  
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. 

The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As a Staff Agent Post-Training MLRE, you will build out our next-gen Agent RL training platform. You’ll build out the platform that will train best-in-class Agents that achieve state of the art results on real enterprise use-cases. 

You’ll integrate cutting edge research into our training stack, enabling MLREs on the Enterprise AI team to deploy use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models. If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you!

You will: 

• Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. 
• Research cutting edge algorithms to integrate directly into our training stack.
• Design solutions that enable complex multi-agent systems to directly learn from both process + outcome based rewards.

Ideally you’d have:

• 5+ years of LLM training in a production environment
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
• PhD or Masters in Computer Science or a related field

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an Applied AI Engineer, you’ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins. Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you’ll use to improve your product’s performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

• Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions 
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.
• Be able and willing to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

Scale AI is seeking a highly technical and strategic Staff / Senior Staff Machine Learning Engineer to act as the Tech Lead (TL) for our next generation of deep research agents for the Enterprise. This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.

The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.

Responsibilities

Technical Leadership & Vision

• Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.
• Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.
• Core Agent Capabilities Development:
• Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.
• Data analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.
• Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base.
• Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.
• Technical Excellence: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.

Team Leadership & Mentorship

• Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.
• Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.
• Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.

Basic Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.
• 8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.
• 2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.
• Deep expertise in Generative AI and Large Language Models (LLMs).
• Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.
• Experience with large-scale distributed systems and real-time data processing.

Preferred Qualifications

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.
• Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.
• Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.
• Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.
• Experience with vector databases and advanced retrieval techniques.
• A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).
• Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.
• Experience driving cross-team technical initiatives that have delivered significant business impact.

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

About the General Agents Team

The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers.

About the Role

As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

You will:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideally you’d have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves:

• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.

About the Role

Anthropic manages one of the largest and fastest-growing accelerator fleets in the industry — spanning multiple accelerator families and clouds. The Accelerator Capacity Engineering (ACE) team is responsible for making sure every chip in that fleet is accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.

As an engineer on ACE, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend.

You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment.

What This Team Owns

The team’s work spans three functional areas. Depending on your background and interests, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap:

• Data infrastructure — collecting, normalizing, and serving the fleet-wide data that powers everything else. This means building pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalizing billing and usage data across cloud providers, and maintaining the BigQuery layer that the rest of the org queries against. Correctness, completeness, and latency matter here.

• Fleet observability — making the state of the accelerator fleet legible and actionable in real time. This means building cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and driving systemic improvements to scheduling and fragmentation. The work sits at the intersection of Kubernetes operations and cross-team coordination.

• Compute efficiency — measuring and improving how effectively every major workload uses the hardware it’s running on. This means instrumenting utilization metrics across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and collaborating directly with system-owning teams to close efficiency gaps.

• Internal compute tooling — building the platforms and interfaces that make capacity data usable across the org. This includes capacity planning tools, workload attribution systems, cost dashboards, and self-service APIs. The consumers are research engineers, infrastructure teams, finance, and leadership — each with different needs and different levels of technical depth. The work involves product thinking as much as engineering: figuring out what people actually need, defining schema contracts, and making the data discoverable.

You will be placed on a pod based on your background and interests. We are especially focused on hiring for Data Platform, but strong candidates for any of the three active pods will move forward.

What You’ll Do

• Build and operate data pipelines that ingest accelerator occupancy, utilization, and cost data from multiple cloud providers into BigQuery. Own data completeness, latency SLOs, gap detection, and backfill automation.

• Develop and maintain observability infrastructure — Prometheus recording rules, Grafana dashboards, and alerting systems — that surface actionable signals about fleet health, occupancy, and efficiency.

• Instrument and analyze compute efficiency metrics across training, inference, and eval workloads. Build benchmarking infrastructure, establish per-config baselines, and work with system-owning teams to improve utilization.

• Build internal tooling and platforms that enable capacity planning, workload attribution, and cluster debugging. The consumers are other engineering teams, finance, and leadership — not external users.

• Operate Kubernetes-native systems at scale — deploying data collection agents, managing workload labeling infrastructure, and understanding how taints, reservations, and scheduling affect capacity.

• Normalize and reconcile data across heterogeneous sources — including AWS, GCP, and Azure billing exports, vendor-specific telemetry formats, and internal systems with different schemas and billing arrangements.

• Collaborate across organizational boundaries with research engineering, infrastructure, inference, and finance teams. Gather requirements from technical stakeholders, translate them into useful systems, and communicate trade-offs to non-technical audiences.

You May Be a Good Fit If You Have

• 5+ years of software engineering experience with a strong track record building and operating production systems. You write code every day — this is a hands-on engineering role, not a planning or coordination role.

• Kubernetes fluency at operational depth — you’ve operated production K8s at meaningful scale, not just written manifests. Comfort with scheduling, taints, labels, node management, and debugging cluster-level issues.

• Data pipeline engineering experience — designing, building, and owning the full lifecycle of production data pipelines. Experience with data warehouses (BigQuery preferred), schema management, streaming ingestion, SLOs for latency and completeness, and a strong instinct for correctness.

• Observability tooling experience — Prometheus, PromQL, and Grafana are in the critical path for this team. Experience writing recording rules, understanding metric semantics, and building monitoring systems that engineering teams actually rely on.

• Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable.

• Familiarity with at least one major cloud provider (AWS, GCP, or Azure) at the infrastructure level — compute, billing, usage APIs, cost management tooling. Multi-cloud experience is a strong plus.

• High autonomy and strong cross-team communication. You can gather your own requirements, navigate ambiguity, and work across organizational boundaries. Scrappiness and ownership matter more than polish.

Strong Candidates May Also Have

• Multi-cloud data ingestion experience — especially working with AWS and GCP APIs, billing exports, or vendor-specific telemetry formats. Experience normalizing data from external providers with different billing arrangements is directly applicable.

• Accelerator infrastructure familiarity — GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience working with ML training/inference systems at the hardware level.

• Performance engineering and benchmarking experience — building benchmark harnesses, establishing baselines, reasoning about compute efficiency (FLOPs utilization, memory bandwidth, interconnect throughput), and working with system teams to diagnose and improve performance.

• Data-as-product thinking — experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just building pipelines, but thinking about how platform data gets consumed.

• Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or large-scale ML environment. FinOps, chargeback systems, or infrastructure cost modeling.

Familiarity with ClickHouse, Terraform, or Rust. ClickHouse is the team’s current streaming store; Terraform for infrastructure-as-code; Rust for high-performance data collection agents.

The opportunity
At Unity, we're building a world-class advertising platform that operates at a massive global scale. The Ads team powers the systems that connect advertisers with creators and players, driving performance, reliability, and growth across our ecosystem.

As a Staff Software Engineer on the Feature Platform team, you'll play a critical role in building the infrastructure that powers machine learning, experimentation, and optimization across our ads ecosystem. You'll design and operate the systems that transform high-volume event data into production-grade feature datasets used for bidding, attribution, and ranking — working at the intersection of distributed systems, platform engineering, and ML infrastructure.

This role goes beyond data processing. You'll own the full software lifecycle of pipeline systems — from architecture and implementation through to reliability, observability, and performance at scale — collaborating closely with ML, backend, and product teams to build durable, high-quality infrastructure that supports both offline training workflows and online feature serving.

This role is ideal for someone who enjoys owning complex systems end-to-end, thinking deeply about correctness and scalability, and building software that other engineering teams depend on.

What you'll be doing

• What You'll Be Doing
• Design, build, and operate scalable, production-grade data pipeline systems and curated feature datasets powering ads optimization and ML
• Own end-to-end offline data flows from raw event ingestion to feature-ready datasets, with strong emphasis on correctness, reproducibility, and SLA compliance
• Develop and maintain large-scale batch and streaming systems (Python / Java / SQL) with a strong focus on performance, cost-efficiency, and reliability
• Build and contribute to our Feature Store platform, including integration with the high-throughput online serving layer (Go-based services)
• Translate complex product and monetization logic into well-engineered, extensible systems serving analytics and machine learning use cases
• Drive improvements in observability, testing frameworks, and quality standards across the platform
• Lead architectural decisions and engineering best practices within the Feature Platform team

What we're looking for

• Strong software engineering fundamentals with deep experience designing and operating large-scale distributed systems in production
• Hands-on experience building production-grade ETL/ELT pipelines using Python, Java, SQL, or similar technologies
• Experience with distributed processing frameworks such as Spark or Flink in both batch and streaming modes, including performance tuning and parallel computation
• Understanding of how offline data systems integrate with online serving layers — feature stores, low-latency APIs, and real-time systems
• Experience with cloud-native environments, containerized systems, Kubernetes, and workflow orchestration tools
• Strong ownership mindset — focused on correctness, observability, and long-term maintainability
• Experience with Go is a plus, particularly for collaboration on high-throughput feature serving services

You might also have

• Experience with ML infrastructure, feature stores, or model training pipelines
• Background in ads, attribution, or monetization systems
• Familiarity with experimentation and metrics infrastructure
• Exposure to high-scale backend or platform engineering

Additional information

• Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

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About the Role

As an Analytics Engineer, you will be an early member of the Data Science & Analytics team building the foundation to scale analytics across our organization. You will collaborate with key stakeholders in Engineering, Product, GTM and other areas to build scalable solutions to transform data into key metrics reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company’s growth. You will also lead your own projects to enable self-serve insights to help teams make data-driven decisions. 

Responsibilities:

• Understand the data needs of stakeholder teams in terms of key data models and reporting, and translate that into technical requirements
• Define, build and manage key data pipelines in dbt that transform raw logs into canonical datasets
• Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data
• Develop insightful and reliable dashboards to track performance of core metrics that will deliver insights to the whole company
• Build foundational data products, dashboards and tools to enable self-serve analytics to scale across the company
• Influence the future roadmap of Product and GTM teams from a data systems perspective
• Become an expert in our organization’s data models and the company's data architecture

You might be a good fit if you have:

• 5+ years of experience as an Analytics Data Engineer or similar Data Science & Analytics roles, preferably partnering with GTM and Product leads to build and report on key company-wide metrics.
• A passion for the company's mission of building helpful, honest, and harmless AI.
• Expertise in building multi-step ETL jobs, building robust data models through tooling like dbt; proficiency with workflow management platforms like Airflow and version control management tools through GitHub.
• Expertise in SQL and Python to transform data into accurate, clean data models.
• Experience building data reporting and dashboarding in visualization tools like Hex to serve multiple cross-functional teams.
• A bias for action and urgency, not letting perfect be the enemy of the effective.
• A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.
• Experience building an Analytics Data Engineering (or similar) function at start-ups. 
• A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress.

WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that unifies identity, intelligence, and omnichannel activation into a single platform – powered by trillions of consumer signals and one of the industry’s largest proprietary databases. Our enterprise clients use the Zeta Marketing Platform (ZMP) to personalize experiences at the individual level across every channel. 

THE ROLE

Our Vertical Applications team builds web applications that bring the power of ZMP to specific industries – Healthcare, Political, Retail, and more. Every vertical comes with its own fascinating challenges: unique compliance requirements, distinct data models, and workflows that genuinely matter to the people using them. It’s the kind of work where you get to learn new domains, solve real problems, and see your applications make a tangible impact. 

You’ll own applications end-to-end: partner with product owners to define the problem, architect the backend, integrate with Zeta’s core platform, build the frontend, ship to production, and ensure operational excellence. We value clean, simple architectures, test-first development, and continuous delivery. AI-assisted development with tools like Cursor, Claude Code, Gemini and Codex is embedded in our everyday workflow, and we’re excited about what agentic engineering unlocks for both development velocity and software quality. 

What You’ll Do 

• Own vertical web applications from idea to production – working closely with product owners, designing the architecture, building it, shipping it, and running it. 

• Architect backend services (Python, Java, Ruby, Node.js) with a focus on simplicity and reusability across verticals, so good patterns compound over time. 

• Build polished frontend experiences in React/TypeScript/Ant Design System that connect seamlessly with backend APIs (REST, Thrift). 

• Ship continuously and confidently through CI/CD, with observability, resilience and reliability built in from the start. 

• Use AI-assisted development tools as a natural part of your workflow to move faster while keeping quality high. 

• Weave AI/LLM capabilities into vertical applications, opening up new possibilities for each domain. 

• Collaborate across teams – mentor fellow engineers, lead technical initiatives, and bring clarity to complex decisions for both technical and non-technical audiences. 

What We’re Looking For 

10+ years of software engineering with a history of owning and operating the systems you build. You’re deeply proficient in at least two of Python, Java, Ruby, or Node.js, with solid React/TypeScript skills on the frontend. Continuous delivery, test-driven development, agile and shift-left are things you genuinely practice – not just checkboxes on a process document. 

You’re comfortable building and operating scalable, distributed, high performant systems and navigating multi-tenant, compliant environments. You’re already using AI-assisted coding tools (Cursor, Claude Code, Gemini, Codex, or similar) and you’re curious about pushing those workflows further.  

You’re a strong communicator who enjoys working directly with product owners, proposing architectures, building consensus across teams, and then making it happen. You’re energized by learning new domains and collaborating with people who care about their craft. 

Nice to Have 

• MarTech or AdTech experience (DSPs, bid stream processing, data-intensive platforms). 

• Domain knowledge in Healthcare, Political, or Retail verticals. 

Tech Stack 

Why You’ll Love It Here 

• Interesting problems across diverse verticals – Healthcare, Political, Retail – on a platform processing trillions of consumer signals. You’ll never be bored. 

• AI-native engineering culture – agentic development isn’t a side experiment, it’s how we build. You’ll be at the forefront of how software teams work in the future. 

• Real ownership and autonomy. We trust our engineers to make great decisions and give them the space to do it. 

• Collaborative, low-ego team that genuinely enjoys working together and learning from each other. 
• Public company (NYSE: ZETA) with strong growth, competitive compensation, equity, and comprehensive benefits. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $220,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-YW1

WHO WE ARE

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that unifies identity, intelligence, and omnichannel activation into a single platform – powered by trillions of consumer signals and one of the industry’s largest proprietary databases. Our enterprise clients use the Zeta Marketing Platform (ZMP) to personalize experiences at the individual level across every channel. 

THE ROLE

Our Vertical Applications team builds web applications that bring the power of ZMP to specific industries – Healthcare, Political, Retail, and more. Every vertical comes with its own fascinating challenges: unique compliance requirements, distinct data models, and workflows that genuinely matter to the people using them. It’s the kind of work where you get to learn new domains, solve real problems, and see your applications make a tangible impact. 

You’ll own applications end-to-end: partner with product owners to define the problem, architect the backend, integrate with Zeta’s core platform, build the frontend, ship to production, and ensure operational excellence. We value clean, simple architectures, test-first development, and continuous delivery. AI-assisted development with tools like Cursor, Claude Code, Gemini and Codex is embedded in our everyday workflow, and we’re excited about what agentic engineering unlocks for both development velocity and software quality. 

What You’ll Do 

• Own vertical web applications from idea to production – working closely with product owners, designing the architecture, building it, shipping it, and running it. 

• Architect backend services (Python, Java, Ruby, Node.js) with a focus on simplicity and reusability across verticals, so good patterns compound over time. 

• Build polished frontend experiences in React/TypeScript/Ant Design System that connect seamlessly with backend APIs (REST, Thrift). 

• Ship continuously and confidently through CI/CD, with observability, resilience and reliability built in from the start. 

• Use AI-assisted development tools as a natural part of your workflow to move faster while keeping quality high. 

• Weave AI/LLM capabilities into vertical applications, opening up new possibilities for each domain. 

• Collaborate across teams – mentor fellow engineers, lead technical initiatives, and bring clarity to complex decisions for both technical and non-technical audiences. 

What We’re Looking For 

10+ years of software engineering with a history of owning and operating the systems you build. You’re deeply proficient in at least two of Python, Java, Ruby, or Node.js, with solid React/TypeScript skills on the frontend. Continuous delivery, test-driven development, agile and shift-left are things you genuinely practice – not just checkboxes on a process document. 

You’re comfortable building and operating scalable, distributed, high performant systems and navigating multi-tenant, compliant environments. You’re already using AI-assisted coding tools (Cursor, Claude Code, Gemini, Codex, or similar) and you’re curious about pushing those workflows further.  

You’re a strong communicator who enjoys working directly with product owners, proposing architectures, building consensus across teams, and then making it happen. You’re energized by learning new domains and collaborating with people who care about their craft. 

Nice to Have 

• MarTech or AdTech experience (DSPs, bid stream processing, data-intensive platforms). 

• Domain knowledge in Healthcare, Political, or Retail verticals. 

Tech Stack 

Why You’ll Love It Here 

• Interesting problems across diverse verticals – Healthcare, Political, Retail – on a platform processing trillions of consumer signals. You’ll never be bored. 

• AI-native engineering culture – agentic development isn’t a side experiment, it’s how we build. You’ll be at the forefront of how software teams work in the future. 

• Real ownership and autonomy. We trust our engineers to make great decisions and give them the space to do it. 

• Collaborative, low-ego team that genuinely enjoys working together and learning from each other. 
• Public company (NYSE: ZETA) with strong growth, competitive compensation, equity, and comprehensive benefits. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $200,000 - $220,000, depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-YW1

As a Staff Backend Engineer at Snorkel, you will set the long-term technical direction and strategy for our Expert Contributor (EC) Platform. You will be responsible for defining and driving complex, multi-quarter architectural initiatives that ensure our services are innovative, scalable, and resilient. Your work will bridge the gap between human expertise and machine learning by enabling domain experts to provide high-signal data for training and refining state-of-the-art models.

Main Responsibilities

• Design and develop mission-critical systems for the end-to-end Expert Contributor (EC) lifecycle, focusing on automated onboarding workflows, performance management, and contributor retention.
• Build robust features and integrations with key third-party services, including platforms for assessments and Employer of Record systems.
• Automate supply and allocation logic to efficiently manage and deploy a high volume of ECs to various data collection projects, ensuring optimal coverage and quality.
• Prototype, optimize, and maintain scalable services to power complex data user management pipelines.
• Set the strategy and architecture for build systems, testing frameworks, and CI/CD pipelines.
• Lead the transition from scheduled releases to a robust, automated continuous deployment framework, taking end-to-end ownership of the release pipeline.
• Build proactively with empathy for both customers and subject matter experts using our tools.
• Mentor and guide Senior and Mid-level engineers on technical design, best practices, and project execution across multiple teams.
• Partner with cross-functional teams to design and deliver improvements to dev-infra, release processes, and internal tooling.
• Engage with product managers, designers, and ML experts to create a phenomenal user experience for data acquisition and refinement.

Qualifications

• 8+ years of software engineering experience developing performant, intuitive, and scalable web application architectures and 2+ years working at a Staff level or equivalent
• Strong background in developer productivity, distributed systems, and cloud platforms (AWS preferred).
• Expertise designing REST for internal services and developers.
• Experience developing and shipping enterprise software products, specifically those focused on data collection, or machine learning applications.
• Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact.
• Ability to work in a fast-paced environment with strong technical communication skills.

Nice to Have

• Experience in hyper-growth startup environments or scaling engineering orgs.
• Experience with AI development workflows, AI-assisted code generation, or SRE automation or strong excitement to learn.
• Prior experience as a Tech Lead Manager (TLM) or equivalent role with a focus on cross-functional technical leadership and mentorship.

Work Schedule

• Work a hybrid schedule with three days per week in our Redwood City HQ or the SF office.

We are looking for an experienced Senior or Staff Engineer for our SRE, InfraSec team, to guide the security of our cloud-based infrastructure. As a Staff SRE, you will be very hands-on technically while also mentoring a small team of SREs.

The InfraSec team collaborates closely with other engineering teams to ensure that our infrastructure adheres to the highest security standards. They build essential security infrastructure and implement controls that reinforce the platform’s security posture.

This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions.This team is deeply involved in the technical aspects of security and the nuances of its actual implementation.

This role can sit in our New York City, Austin, Seattle or San Francisco offices on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones.

Responsibilities:

Cloud Security Design and Implementation:  

• Help lead the design and deployment of security solutions for cloud platforms (AWS, Azure, GCP), including network and compute security, identity management, and cloud security posture management (CSPM)

Automation and Monitoring:  

• Build automated solutions for real-time security monitoring, logging, and alerting in cloud environments. Leverage native cloud services and third-party tools for runtime security monitoring and anomaly detection

Security Tooling:

• Evaluate, implement, and manage cloud-native security tools and platforms for endpoint security, identity management (IAM), and CSPM 

Qualifications:

Experience:  

• 6+ years of experience in SRE, infrastructure engineering or similar role, with a strong focus on security work, with ideally 2+ years in a senior or staff engineering role

Security Mindset:

• A comprehensive understanding of all facets of cloud environment security, spanning from foundational OS networking layers to cloud provider configurations. Proven experience in leading projects within security-focused areas, such as runtime scanning, security observability, CSPM, and more

Cloud Expertise:  

• Strong experience with at least one cloud platform (AWS, Azure, GCP), including expertise in IAM, VPC networking, security groups, and cloud security tools (e.g., GuardDuty, Security Hub, CloudTrail)

Coding/Automation:  

• Proficiency in at least one programming language (we use Golang but are language agnostic when it comes to hiring ) and experience with infrastructure-as-code tools (Terraform, CloudFormation, Ansible) to automate security configurations and processes

Linux and Networking

• Understanding of the underlying Linux and networking concepts, including low-level fundamentals, and how they work together in complex systems

Communication and Leadership Skills:  

• Strong ability to explain complex security concepts to both technical and non-technical teams. Ability to lead a small technical team and ensure success both meeting the team goals as well as personal growth for all team members

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 1263064630

We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure.

The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards.

This role can be based out of our New York City, Austin, Seattle or San Francisco offices, or work fully remotely on standard East Coast business hours.

Responsibilities:

• Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP
• Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour
• Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.)
• Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code
• Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership
• Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services

Qualifications:

You might be a great fit if you match some of the following:

• 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work
• Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations and processes
• A deep understanding of Linux and networking concepts, including low-level fundamentals, and how they work together in complex systems
• Experience building security-related features or platforms such as runtime monitoring, CSPM, or vulnerability management
• Experience with a cloud provider (AWS, GCP, or Azure) and their security best practices and building blocks
• Hands-on experience with Kubernetes and its security ecosystem (e.g. RBAC, OPA/Gatekeeper, Kyverno, eBPF, Falco, Tetragon)
• A systems mindset: you think about failure modes, performance, observability, and operability alongside security and correctness
• Strong communication skills and the ability to explain complex security concepts and tradeoffs to both technical and non-technical stakeholders

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 2263171228

About the Role

The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.

Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale.

Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.

What You'll Do

• Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
• Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps
• Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
• Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
• Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region
• Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads

You May Be a Good Fit If You:

• Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
• Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
• Are curious about LLM serving; prior inference or ML experience is not required
• Thrive in cross-functional collaboration with both internal teams and external partners
• Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
• Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description

Strong Candidates May Also Have Experience With

• Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
• Have experience working with external partners to align goals and deliver impact
• Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
• Solid understanding of multi-region deployments, geographic routing, and global traffic management
• Proficiency in Python or Rust

About the Role:

We're looking for seasoned full-stack software engineers to join the teams behind Gusto's customer-facing products — the features and experiences that small business owners and their employees rely on every day.

As a Staff Software Engineer, you'll operate across the full product lifecycle: shaping features from early spec and design through to launch and long-term iteration. That means writing clean frontend code, designing and building reliable backend APIs, influencing product direction, and taking ownership of what happens after a feature ships. 

If you're drawn to work that combines technical craft with real-world impact — helping power the livelihoods of millions using Gusto products — join us!

Here’s what you’ll do day-to-day:

• Design, build, and test Gusto core products such as Payroll, Benefits, HR, Retirement, Gusto Money, Gusto Solo, and Gusto Pro, among others
• Mentor other engineers to help solve some of the hardest technical problems out there in very complex domains and at a large scale
• Help scale one of the largest Ruby/Rails and Javascript/React applications in the world
• Collaborate with our Product Management, Data, Design, and Platform Engineering teams to understand customer pain points, come up with solutions, and then prototype, iterate, and launch daily
• Build products that our customers genuinely love

Here’s what we’re looking for:

• Successful applicants typically have 8+ years of software development experience
• Experience building scalable solutions that eliminate customer pain; passion for creating memorable experiences for customers
• Experience leveraging AI tools or systems to accelerate development, improve testing, and deliver new product capabilities
• Curiosity and experimentation with emerging AI frameworks, applying and sharing best practices to evaluate and scale AI use safely across teams
• Experience owning multi-quarter projects that solve complex engineering problems and make measurable customer impact at scale
• Experience with large scale refactors, performance and reliability issues, and a strong sense of ownership over all aspects of your product area
• Ability to mentor engineers to maximize their performance and impact

Others:

• Experience in, or interest working in, Ruby on Rails 
• Appreciation for a collaborative, test-driven environment
• Ability to build well-structured, maintainable, well-documented code
• Ability to effectively communicate across engineering teams and with business stakeholders

Do you prefer platform development instead? Check out our Staff Software Engineer, Core Platforms job listing. 

Please note that a two day travel to a Gusto office for onboarding is required for this position. If you have any questions regarding this requirement, please share with your recruiter.

Our cash compensation amount for this role is targeted at $163,000–$204,000 in Denver & most remote locations, and $197,000–$247,000 for San Francisco & New York. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.

Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

The Role

Block is building the next generation of commerce experiences for merchants and PSPs through Afterpay, Cash App Pay, Clearpay, and Cash App Afterpay. As part of Block's Solutions Engineering team, you will be a senior technical leader driving complex partner and merchant integrations. You'll work directly with business development, sales, and product teams to deeply understand customer needs, showcase our APIs and services, and solve challenging technical problems that accelerate adoption.

You Will

• Partner with Sales & Account Management to support sellers integrating with our platform, and co-sell Cash App Afterpay's Developer Platform.
• Design and deliver technical solutions, including building proof-of-concepts, custom reports, sample integrations, and troubleshooting complex issues.
• Be a trusted technical advisor - translating business requirements into scalable integration approaches and advocating for best practices.
• Collaborate with product and engineering teams to surface partner feedback and influence the roadmap.
• Create compelling demos, presentations, and technical deep dives for both executives and engineering.
• Communicate product features, updates, and technical guidance across internal and external audiences.

You Have

• 7+ years of experience in technical customer-facing roles (partner engineering, solutions architecture, sales engineering, or similar), working with enterprise merchants or global partners.
• Deep hands-on technical expertise - comfortable building with APIs, debugging integrations, and guiding developers through complex implementations.
• Prior professional experience with full-stack development and proficiency in at least one programming language.
• Experience leading technical projects end-to-end in globally distributed, multicultural teams.
• A willingness to travel for onsite client meetings (10-20%)

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page.

While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted.

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.

Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

The Role

Block is building the next generation of commerce experiences for merchants and PSPs through Afterpay, Cash App Pay, Clearpay, and Cash App Afterpay. As part of Block's Solutions Engineering team, you will be a senior technical leader driving complex partner and merchant integrations. You'll work directly with business development, sales, and product teams to deeply understand customer needs, showcase our APIs and services, and solve challenging technical problems that accelerate adoption.

You Will

• Partner with Sales & Account Management to support sellers integrating with our platform, and co-sell Cash App Afterpay's Developer Platform.
• Design and deliver technical solutions, including building proof-of-concepts, custom reports, sample integrations, and troubleshooting complex issues.
• Be a trusted technical advisor - translating business requirements into scalable integration approaches and advocating for best practices.
• Collaborate with product and engineering teams to surface partner feedback and influence the roadmap.
• Create compelling demos, presentations, and technical deep dives for both executives and engineering.
• Communicate product features, updates, and technical guidance across internal and external audiences.

You Have

• 7+ years of experience in technical customer-facing roles (partner engineering, solutions architecture, sales engineering, or similar), working with enterprise merchants or global partners.
• Deep hands-on technical expertise - comfortable building with APIs, debugging integrations, and guiding developers through complex implementations.
• Prior professional experience with full-stack development and proficiency in at least one programming language.
• Experience leading technical projects end-to-end in globally distributed, multicultural teams.
• A willingness to travel for onsite client meetings (10-20%)

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page.

While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted.

Join the IT Engineering team as a Staff AI Enablement Engineer, where you will serve as the primary driver of AI enablement and solutions engineering across all departments at Checkr. This is a highly visible, hands-on role that blends deep technical expertise with a passion for teaching and empowering others. You will lead the charge on understanding team-specific requirements, configuring and evaluating AI tools, building bespoke AI-powered solutions, and standing up templatizable workflows that scale across the organization. From running office hours and hackathons to creating reusable resources and training materials, you will be the go-to person for helping every team at Checkr unlock the full potential of AI.

What you’ll do:  

• Requirements Gathering & Enablement: Embed with internal teams across departments to deeply understand their workflows, gather requirements, identify high-impact AI use cases, and translate business needs into actionable technical solutions.
• Lead Office Hours & Hackathons: Own and facilitate recurring AI office hours for drop-in support and guidance. Design and lead company-wide AI hackathons that inspire experimentation, knowledge sharing, and the discovery of innovative use cases.
• AI Tool Configuration & Evaluation: Evaluate, configure, and recommend the right AI tools and platforms for the organization. Stay on top of the rapidly evolving AI tooling landscape and make informed build-vs-buy recommendations.
• Build Bespoke AI Solutions: Design, develop, and deploy custom AI solutions tailored to specific team needs—leveraging LLMs, RAG architectures, agentic workflows, and automation frameworks to solve real business problems.
• Create Resources & Artifacts: Develop reusable playbooks, prompt libraries, workflow templates, how-to guides, and reference architectures that enable teams to self-serve on AI adoption.
• Templatize AI Workflows: Architect and implement standardized, templatizable AI workflows that can be adapted and deployed across multiple teams and use cases, driving consistency and scale.
• Training & Teaching: Lead hands-on training sessions, workshops, and demos to teach teams how to effectively use AI tools and integrate them into their day-to-day work. Act as a force multiplier by building AI fluency organization-wide.
• Cross-Functional Collaboration: Partner closely with Engineers, Business Systems, Security, Data Engineering, and other AI Solutions Engineers to integrate AI technologies into existing systems, ensuring security, compliance, and scalability.
• Strategic Planning & Roadmapping: Contribute to the AI strategy and roadmap at the organizational level, aligning initiatives with business priorities and ensuring AI investments deliver maximum value.
• Communicate & Evangelize: Present findings, demo solutions, share progress updates, and advocate for AI adoption with stakeholders ranging from individual contributors to executive leadership.

What you’ll bring:  

• Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience. A graduate degree is a plus.
• 5-7+ years of experience in engineering, solutions engineering, or technical enablement roles, with a track record of deploying solutions that measurably enhance productivity.
• 4+ years of hands-on experience developing AI-centric products and solutions, including machine learning, generative AI, LLMs, RAG architectures, agentic frameworks, and prompt engineering.
• Deep proficiency in Python and experience with AI frameworks and tools such as LangChain, LangGraph, LlamaIndex, OpenAI API, and similar; familiarity with containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure).
• Demonstrated ability to lead enablement programs—including running office hours, hackathons, training sessions, and creating scalable documentation and resources.
• Proven experience gathering requirements from non-technical stakeholders and translating them into well-scoped technical solutions.
• Exceptional ability to tackle open-ended, ambiguous problems in unstructured environments, synthesizing complex information into actionable plans and deliverables.
• Strong communication and presentation skills, with the ability to make complex AI concepts accessible to diverse audiences—from engineers to executives.
• A builder’s mindset: you are equally comfortable architecting a solution, writing production code, creating a training deck, and facilitating a workshop.
• A deep passion for AI and a genuine desire to help others harness its potential to transform how they work.

What you’ll get:

• A fast-paced and collaborative environment
• Learning and development allowance
• Competitive compensation and opportunity for advancement
• 100% medical, dental, and vision coverage
• Up to $25K reimbursement for fertility, adoption, and parental planning services
• Flexible PTO policy
• Monthly wellness stipend, home office stipend

#LI-TD1

About the Role

This is a research engineering role with direct production impact. You won’t be publishing ideas in isolation—you will translate new RL algorithms, scheduling methods, and inference optimizations into production-grade systems that power Together’s API. Success in this role means shipping measurable improvements in latency, throughput, cost, and model quality at scale. We are looking for researchers who enjoy owning systems end-to-end and turning frontier ideas into robust infrastructure.

The Core ML (Turbo) at Together AI team sits at the intersection of efficient inference (algorithms, architectures, engines) and post‑training / RL systems. We build and operate the systems behind Together’s API, including high‑performance inference and RL/post‑training engines that can run at production scale.

Our mandate is to push the frontier of efficient inference and RL‑driven training: making models dramatically faster and cheaper to run, while improving their capabilities through RL‑based post‑training (e.g., GRPO‑style objectives). This work lives at the interface of algorithms and systems: asynchronous RL, rollout collection, scheduling, and batching all interact with engine design, creating many knobs to tune across the RL algorithm, training loop, and inference stack. Much of the job is modifying production inference systems—for example, SGLang‑ or vLLM‑style serving stacks and speculative decoding systems such as ATLAS—grounded in a strong understanding of post‑training and inference theory, rather than purely theoretical algorithm design.

You’ll work across the stack—from RL algorithms and training engines to kernels and serving systems—to build and improve frontier models via RL pipelines. People on this team are often spiky: some are more RL‑first, some are more systems‑first. Depth in one of these areas plus appetite to collaborate across (and grow toward more full‑stack ownership over time) is ideal.

Responsibilities

• Advance inference efficiency end‑to‑end
• Design and prototype algorithms, architectures, and scheduling strategies for low‑latency, high‑throughput inference.
• Implement and maintain changes in high‑performance inference engines (e.g., SGLang‑ or vLLM‑style systems and Together’s inference stack), including kernel backends, speculative decoding (e.g., ATLAS), quantization, etc.
• Profile and optimize performance across GPU, networking, and memory layers to improve latency, throughput, and cost.
• Unify inference with RL / post‑training
• Design and operate RL and post‑training pipelines (e.g., RLHF, RLAIF, GRPO, DPO‑style methods, reward modeling) where 90+% of the cost is inference, jointly optimizing algorithms and systems.
• Make RL and post‑training workloads more efficient with inference‑aware training loops—for example, async RL rollouts, speculative decoding, and other techniques that make large‑scale rollout collection and evaluation cheaper.
• Use these pipelines to train, evaluate, and iterate on frontier models on top of our inference stack.
• Co‑design algorithms and infrastructure so that objectives, rollout collection, and evaluation are tightly coupled to efficient inference, and quickly identify bottlenecks across the training engine, inference engine, data pipeline, and user‑facing layers.
• Run ablations and scale‑up experiments to understand trade‑offs between model quality, latency, throughput, and cost, and feed these insights back into model, RL, and system design.
• Own critical systems at production scale
• Profile, debug, and optimize inference and post-training services under real production workloads, taking research ideas all the way to stable, measurable improvements in deployed systems.
• Drive roadmap items that require real engine modification—changing kernels, memory layouts, scheduling logic, and APIs as needed.
• Establish metrics, benchmarks, and experimentation frameworks to validate improvements rigorously.
• Provide technical leadership (Staff level)
• Set technical direction for cross‑team efforts at the intersection of inference, RL, and post‑training.
• Mentor other engineers and researchers on full‑stack ML systems work and performance engineering.

Requirements

We don’t expect anyone to check every box below. People on this team typically have deep expertise in one or more areas and enough breadth (or interest) to work effectively across the stack. The closer you are to full‑stack (inference + post‑training/RL + systems), the stronger the fit—but being spiky in one area and eager to grow is absolutely okay.

You might be a good fit if you:

• Have a bias toward implementation and shipping—you are excited to modify real engines and services, not just prototype in research code.
• Have strong expertise in at least one of the following, and are excited to collaborate across (and grow into) the others:
• Systems‑first profile: Large‑scale inference systems (e.g., SGLang, vLLM, FasterTransformer, TensorRT, custom engines, or similar), GPU performance, distributed serving.
• RL‑first profile: RL / post‑training for LLMs or large models (e.g., GRPO, RLHF/RLAIF, DPO‑like methods, reward modeling), and using these to train or fine‑tune real models.
• Model architecture design for Transformers or other large neural nets.
• Distributed systems / high‑performance computing for ML.
• Are comfortable working from algorithms to engines:
• Strong coding ability in Python
• Experience profiling and optimizing performance across GPU, networking, and memory layers.
• Able to take a new sampling method, scheduler, or RL update and turn it into a production‑grade implementation in the engine and/or training stack.
• Have a solid research foundation in your area(s) of depth:
• Track record of impactful work in ML systems, RL, or large‑scale model training (papers, open‑source projects, or production systems).
• Can read new RL / post‑training papers, understand their implications on the stack, and design minimal, correct changes in the right layer (training engine vs. inference engine vs. data / API).
• Operate well as a full‑stack problem solver:
• You naturally ask: “Where in the stack is this really bottlenecked?”
• You enjoy collaborating with infra, research, and product teams, and you care about both scientific quality and user‑visible wins.

Minimum qualifications

• 3+ years of experience working on ML systems, large‑scale model training, inference, or adjacent areas (or equivalent experience via research / open source).
• Advanced degree in Computer Science, EE, or a related field, or equivalent practical experience.
• Demonstrated experience owning complex technical projects end‑to‑end.

If you’re excited about the role and strong in some of these areas, we encourage you to apply even if you don’t meet every single requirement.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

About the Role

Together AI is seeking a Staff Backend Engineer to own the technical vision, architecture, and execution of the commerce platform powering Together's Cloud products. As a staff engineer on the Commerce Engineering team, you will set the engineering direction for mission-critical capabilities — including usage-based billing, payment processing, customer-facing analytics, and product entitlements — while raising the bar for the engineers around you.

This role is ideal for a seasoned engineer who can operate at multiple altitudes: driving system design and long-term architecture decisions while staying hands-on in code. You'll be the connective tissue between engineering, product, finance, and go-to-market — translating complex business requirements into durable, scalable backend primitives that directly impact revenue and customer experience. You'll be expected to define not just what we build, but how we build it well.

Requirements

• 8+ years of experience building large-scale, fault-tolerant API-driven services and backend systems
• Demonstrated track record of tech lead or staff-level scope — owning system architecture decisions, influencing team direction, and delivering multi-quarter initiatives
• Deep expertise in designing relational database schemas and backend APIs that support complex product and business requirements at scale
• Strong experience leading and influencing cross-functional teams — comfortable partnering with product, finance, and non-technical stakeholders
• Expert-level proficiency in one or more of Golang, TypeScript, Python, C++, or Java
• Deep knowledge of distributed systems tradeoffs: consistency, availability, fault tolerance, and performance at scale
• Strong understanding of low-level systems concepts: multi-threading, memory management, networking, storage, and I/O
• Experience with infrastructure as code (Terraform, AWS CDK, Pulumi) and mature CI/CD workflows
• Experience with payment processors (e.g. Stripe) and billing systems strongly preferred
• Experience with Kubernetes and containerized deployments a plus
• Bachelor's or Master's degree in Computer Science, Computer Engineering, or equivalent practical experience

Responsibilities

• Define and own the technical roadmap for Together's monetization and billing pipeline infrastructure, spanning usage metering, contract billing, entitlements, spend governance, and payments processing
• Lead architecture reviews for major systems investments, ensuring long-term scalability, correctness, and maintainability across the commerce stack
• Drive cross-functional alignment with Product, Finance, and Go-To-Market teams — translating business strategy into clear engineering requirements and system designs
• Mentor and grow engineers on the team through design feedback, code reviews, technical coaching, and setting high standards for craft
• Own data modeling and schema design for core commerce entities, making principled tradeoffs between flexibility, performance, and correctness
• Establish and evolve API contracts in collaboration with client engineering teams, enabling high-quality customer-facing product experiences
• Champion reliability and scalability — lead incident response, drive postmortems, and systematically improve the resilience of commerce APIs and distributed systems
• Identify and reduce technical debt proactively, balancing pragmatic delivery with sustainable engineering practices

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $230,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy