We are looking for a detail-oriented, strategic, and outcomes-driven Principal Analyst to join our GTM Operations team, supporting processes and systems across our global go-to-market (GTM) organization — including Customer Success, Sales, and other customer-facing teams.

You will act as a senior thought partner to GTM leadership, owning complex, cross-functional initiatives that improve operational efficiency, drive data-informed decision making, and scale our customer lifecycle processes globally. This role requires the ability to influence senior stakeholders across functions and regions, navigate ambiguity, and turn strategy into measurable business impact.

We are looking to speak to candidates who are based in the United States for our hybrid or remote working models.

As a Principal GTM Operations Analyst, you will:

• Partner with senior leaders across Customer Success, Sales, and other GTM teams to design, optimize, and scale core processes across the customer lifecycle, including customer engagement, renewals, and account management workflows
• Own the strategy, design, and continuous improvement of global operational processes, ensuring scalability, consistency, and alignment to GTM and company priorities across regions
• Translate ambiguous business problems into clear operational and technical requirements, working closely with CRM Engineering and GTM Systems teams to deliver high-impact system and tooling improvements
• Drive material improvements in activity tracking, customer health signals, lifecycle workflows, and other key operational insights to enable better customer engagement, planning, and outcomes
• Define, instrument, and monitor key performance indicators and operational metrics to evaluate GTM initiatives and provide clear, data-driven recommendations to leadership
• Lead complex, cross-functional programs from problem definition through execution, including roadmap ownership, stakeholder alignment, risk management, and executive updates
• Establish and maintain governance frameworks, operating cadences, and documentation to ensure process clarity, adoption, and continuous improvement across global GTM teams
• Proactively identify operational gaps and inefficiencies, quantify impact, and propose data-driven solutions that improve GTM productivity, customer outcomes, and revenue performance
• Serve as a mentor and senior partner within the GTM Operations team, helping raise the bar on process design, execution, and cross-functional collaboration
• Bring forward new ideas, tools, and best practices that improve how we scale GTM operations globally

The Ideal Candidate has:

• Bachelor’s Degree in Business, Economics, Finance, Computer Science, or a related field
• 7+ years of work experience in GTM Operations, Revenue Operations, Sales Operations, Customer Success Operations, Business Operations, or a related field
• Demonstrated ability to solve complex, ambiguous problems end-to-end — from framing and analysis through recommendation, execution, and measurement
• Proven track record of designing and scaling GTM processes and driving measurable process and productivity improvements for a global GTM organization
• Experience leading cross-functional projects and programs with multiple senior stakeholders, with a strong ability to influence without direct authority
• Excellent communication skills, including the ability to synthesize complex concepts into clear narratives and influence both business and technical stakeholders, including senior leaders
• Deep experience with CRM systems, particularly Salesforce, and familiarity with GTM tooling
• Experience in a consumption/pay-as-you-go business model is a plus
• Strong organizational skills and the ability to manage multiple, competing priorities in a fast-paced, globally distributed organization
• A proactive, ownership-minded approach and the ability to operate with a high degree of autonomy and accountability for outcomes

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 over 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: 1273423069

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.

The Team

Our engineering team builds systems that interact with some of the most complex software  ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. 

We are looking for a client-obsessed AI Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize. While we are a remote-first company, the nature of this role requires candidates to be based in the San Francisco Bay area/PST time zone.

What You’ll Do

• Work closely with some of the most sophisticated ML / GenAI teams in the world.
  • You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders.
• Advise on GenAI and ML best practices 
• Give ML and LLM product demos to technical and business stakeholders
• Run strategic business reviews for customers in partnership with our sales team
• Interface with our pre-sales engineering team to gather client goals and KPI’s.
• Partner with our product and engineering teams to help drive the product roadmap
• Spearhead new opportunities within existing accounts to help drive expansions.

What We’re Looking For

Note: Even if you do not check every single box, we still encourage you to apply! 

• Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
• Comfortable working in public Cloud environments (AWS, Azure, GCP)
• Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
• Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
• Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
• Understanding of GenAI concepts and application evaluation + development lifecycle  
• Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
• Strong Communication Skills - Ability to simplify complex, technical concepts.
• A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.

Bonus Points, But Not Required

• Previous engineering experience in:
  • Data Science
  • MLOps
  • ML Frameworks
  • LLM / Agentic frameworks
• Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
• Prior experience working with applications deployed with Kubernetes
• Prior experience demoing technical products to both business and technical audiences

The estimated annual salary and variable compensation for this role is between $125,000 - $175,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.

While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.

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

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As a Security Operations Engineer at Brex, you will focus on preventing, detecting and responding to security threats across Brex's corporate and cloud environments. You will use existing systems and develop tools to improve our security capabilities. Our team is responsible for functions across corporate security, detection & response and infrastructure security domains; and we perform systems engineering and automation to support those functions. 

Security Operations is part of our wider Trust & IT organization which means you will have the opportunity to work closely with Application Security, Corporate Engineering, GRC and IT and to improve security configurations, drive positive employee behaviors and generally work to prevent events from becoming incidents. You will also help build and maintain our team’s open source project Substation and have the opportunity to contribute to the Brex Tech Blog. You’ll be part of a team that actively contributes to the wider security community and has a commitment to mentorship and engineering excellence.

We’re looking for individuals with a strong background and interest in detecting, responding to, and resolving security incidents and security challenges. You should be comfortable dealing with lots of moving pieces, changing priorities, and new technologies, while having a keen eye for detail. Most importantly, you should be enthusiastic about working with a variety of backgrounds, roles, and people across Brex. Building a world-class financial service requires world-class security.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Work on a highly cross-functional team to prevent, detect and respond to security threats across Brex's corporate and cloud environments
• Perform security incident response, investigation, remediation, and documentation, participate in periodic threat hunting and security exercises
• Leading, scoping and building features, participate in designing, and maintaining tools and systems which support the team’s domains – corporate security, detection & response and infrastructure security 
• Collaborating and partnering with engineering and operations teams to drive remediation of security issues, while balancing prioritization of those security issues within SLA and teams’ respective backlogs
• Caring about secure system design, valuing building things correctly, an understanding of a MVP approach and an empathetic mindset when working with others

Requirements

• Bachelor’s degree in Computer Science, Engineering or related field OR equivalent training / fellowship OR 5+ years work experienceExperience working in a corporate security, detection & response or infrastructure security role with responsibilities for security alert triage and security incident response 
• Familiarity with CI/CD systems and DevOps workflows (e.g. Buildkite, Flux, Git, Terraform) in cloud environments (e.g. AWS, Azure, GCP)
• Experience with deploying and maintaining some of the security services and tools owned by the team (e.g. - SIEM, data pipelines, SOAR, domain monitoring, endpoint tooling, email protection tooling, cloud security tools)
• While not primarily a development role, the team develops and maintains tools written in Go and Python, so experience with coding is required
• You thrive in a collaborative environment filled with a diverse group of people with different expertise and backgrounds. We currently have around 30 nationalities represented with more than ½ the company working in a country different from the one they grew up in.

Bonus points

• Proficiency with Go and other programming languages 
• Experience with securing distributed systems in AWS, cloud and Kubernetes environments
• Contributions to the wider technical community (open source, public research, mentorship, community organizing, blogging, presentations, etc)

Compensation

The expected salary range for this role is $192,000 - $240,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our Vancouver office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000 CAD. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our Seattle office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Engineering

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

Brex’s Governance, Risk, and Compliance function is at an exciting and pivotal point in our maturity journey and we’re seeking a team member who can seamlessly bridge compliance expertise with technical execution. As a Senior GRC Engineer, you will drive critical GRC processes that mitigate risk, keep us compliant, and build trust with our customers and partners. You'll evolve the technical foundation of our Trust program by automating security controls, building integrations between security tools and GRC platforms, and creating scalable processes that enable Brex to maintain compliance efficiently as we expand into new markets. You'll work at the intersection of security, engineering, and compliance — translating regulatory requirements into technical solutions and building automation that eliminates manual toil.

You'll leverage your deep understanding of SOC 2, PCI DSS, ISO 27001, AI governance frameworks, and others to both design controls for emerging compliance requirements and mature existing programs through automation and continuous monitoring. You’ll support Trust Assurance, Third Party Risk Management, and other Security Risk Management initiatives. Working with our Engineering, Infrastructure, and Product teams, you'll translate compliance frameworks into technical controls and build automated systems that help us achieve world-class security as Brex expands.

Your contributions will directly accelerate Brex's maturity. You'll design workflows using Tines, build integrations between security and GRC systems, and create dashboards for security metrics. You'll implement controls across the technology stack, support multiple audits (SOC 2, PCI DSS, SOX/ITGC, FINRA, ISO), and contribute to AI governance framework implementation (ISO 42001, NIST AI RMF, EU AI Act).

You'll have autonomy to build innovative solutions, collaborating cross-functionally to implement controls that enable growth while communicating technical concepts effectively across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Manage and scale IT infrastructure, services and tooling
• Work with a diverse group of  IT partners to optimize our provided services
• Implement new services in support of Information Technologies vision
• Scale our services by implementing configuration as code via Terraform providers or APIs
• Operationalize and upskill IT and its partners by producing documentation and leading training sessions
• Evangelize best practices both internally and externally facing

Requirements

• 5+ years of experience in GRC, IT Governance, or Security Engineering with a strong track record of automating manual compliance workflows.
• Deep experience with security frameworks such as SOC 2, PCI DSS, ISO 27001, and NIST CSF, specifically within cloud-native environments.
• Technical proficiency in Python (or similar scripting languages) and experience building integrations using APIs to connect security tools with GRC systems. You can read code, design integrations, and understand technical implementations.
• Builder mindset with the ability to design and implement automated control testing, continuous monitoring, and data-driven security metrics. You see manual processes and immediately think about how to automate them.
• Exceptional cross-functional collaboration and communication skills. You can translate complex compliance requirements into technical specifications that engineering teams can actually implement and influence stakeholders across technical and non-technical domains.
• Strong systems thinking. You have the ability to design scalable GRC architectures that grow with the company, rather than just solving for the immediate audit.
• Bias for action. You’re a self-starter who ships solutions quickly and iterates based on feedback. 

Bonus points

• Previous experience in Fintech or banking environments navigating complex regulatory landscapes.
• Hands-on experience with Tines or other SOAR platforms to automate security operations.
• Familiarity with AI/ML governance frameworks (NIST AI RMF, ISO 42001) or securing agentic systems.
• Deep knowledge of Cloud Security (AWS/GCP), infrastructure-as-code (Terraform), or DevSecOps practices.
• Relevant industry certifications such as CISSP, CISA, or CCSP.
• Experience building metrics dashboards for security visualization and reporting.
• Active contributions to the GRC or Security community through open-source projects or public research.

Compensation

The expected salary range for this role is $153,600 - $192,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Our Internal Data team powers decisions and applications across MongoDB, supporting teams in Go-to-Market (GTM), Product and Technology, Finance, and HR. As MongoDB scales, we are making a significant investment in becoming a truly Data-Driven Enterprise — one built on trusted, governed golden data assets, world-class self-serve capabilities, and AI-ready data infrastructure. This is a rare opportunity to lead a high-visibility, company-defining initiative that will transform how MongoDB teams access, trust, and act on data.

This role can be based in one of our major U.S. offices (New York City, Austin, Palo Alto, or San Francisco) under our hybrid working model, or remotely within the United States.

As Senior Director of Data Product Management, you will own the vision, strategy, and execution of MongoDB's internal data product portfolio, with an initial focus on Go-to-Market (GTM) functions including Sales, Marketing, and Customer Success. You will lead and grow a team of four Product Managers, partnering deeply with Data Pipeline, Platform Engineering, Data Architecture, and Data Governance teams to deliver the data products MongoDB teams rely on every day. These products span data pipelines, canonical datasets, dashboards, APIs, ML models, and self-serve frameworks that power analytics, AI, and business decision-making at scale.

This role is ideal for a seasoned data product leader who brings both strategic vision and operational depth — someone who can engage credibly with C-suite stakeholders, inspire a high-performing team, and drive a complex, multi-workstream enterprise initiative from vision to measurable impact.

Responsibilities

• Own and communicate a compelling, multi-year product vision and strategy for MongoDB's internal data products, anchored in the goal of building a Data-Driven Enterprise with trusted golden data and strong self-serve capabilities
• Serve as a thought partner and key point of contact for C-suite and executive stakeholders, translating enterprise data strategy into a clear, prioritized product roadmap
• Lead, mentor, and grow a team of Product Managers, fostering a high-performance culture of ownership, curiosity, and impact
• Champion the development of canonical, single-source-of-truth golden data assets that serve as the single source of truth for Customer, Product, People and Finance data, breaking down siloes and cultivating a common language across metrics business-wide
• Drive the build-out of self-serve data capabilities that empower business users to access, explore, and act on trusted data with minimal friction
• Partner with leadership across the company to identify and prioritize the highest-value opportunities where data products can improve decision-making, automate workflows, and accelerate growth
• Work across Data Engineering, Architecture, Platform, and Governance teams within IT as well as our key partners in Analytics & Data Science to ensure data products are scalable, reliable, and aligned with enterprise data standards
• Define and own success metrics for the data product portfolio, using data to demonstrate business impact and continuously raise the bar
• Establish and evolve product development practices across the team, including roadmap planning, backlog management, agile delivery, and cross-functional coordination
• Drive organization-wide adoption of data products through effective storytelling, clear documentation, enablement programs, and change management

Requirements

• 10+ years of product management experience, with at least 3–5 years in a senior leadership role managing product managers and delivering data products or data platforms at scale
• Demonstrated experience leading large, strategic, enterprise-wide data democratization initiatives with executive visibility and cross-functional complexity
• Deep understanding of modern data ecosystems, including data pipelines, lakehouse and medallion architectures, analytics platforms, and data governance frameworks
• Exceptional communication and executive presence, with the ability to translate complex technical strategies into compelling narratives for C-suite audiences
• Proven ability to define and execute a vision for trusted, governed data assets and scalable self-serve data capabilities
• Experience building and scaling self-serve analytics and data enablement programs
• Experience partnering with and influencing partner organizations across the company at the leadership level
• Strong people leadership skills, with a track record of developing and retaining high-performing product talent
• Ability to operate effectively in fast-paced, ambiguous environments, balancing long-term strategic thinking with near-term execution

Nice to Have

• Background in analytics, data science, or data engineering
• Familiarity with metadata management, data discoverability, or data catalog tooling
• Exposure to AI/ML product development in the context of enterprise data platforms

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 over 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: 1273386452

About the Role

We are seeking a GRC Automation Lead to join our GRC organization and build the technical foundation for how we scale our risk and compliance programs. In this role, you will lead the team that designs and implements automated workflows, data pipelines, and integrations that transform manual compliance processes into scalable engineering systems. 

This is a greenfield opportunity to establish the team, architecture, and integrations that will define how we approach governance, risk, and compliance at Anthropic. The core challenge is a data problem: compliance information lives across dozens of systems—cloud infrastructure, identity providers, HR platforms, ticketing tools, code repositories—and your job is to design systems that bring it together, normalize it, and make it actionable. Success in this role comes from understanding how systems connect and how data flows between them, not from writing code yourself.

At Anthropic, you'll also have a unique advantage: the ability to design AI-powered workflows where Claude acts as an extension of your team, handling tasks that would traditionally require additional headcount or manual effort. You'll need ingenuity to identify where agentic AI can accelerate evidence collection, interpret unstructured data, triage compliance gaps, and augment human judgment in risk assessments. Working closely with Security, IT, and Engineering teams, you'll translate compliance and regulatory requirements into solutions that support audit programs including SOC 2, ISO, HIPAA, and FedRAMP, building systems that combine traditional automation with AI capabilities to achieve scale that wouldn't otherwise be possible.

Responsibilities: 

• Lead the team that establishes foundational GRC processes and architecture. Design and build automated workflows for risk management and compliance, creating scalable systems that enable continuous monitoring as Anthropic grows.
• Build data pipelines that aggregate risk, control, and asset information from across our technology stack. This means solving hard data integration problems: mapping disparate schemas, handling inconsistent data quality, and creating unified views of compliance posture through dashboards and reporting tools.
• Inform GRC platform strategy and implementation: in partnership with other programs, evaluate, select, and deploy tooling that meets our compliance requirements.
• Translate written policies and compliance requirements into policy-as-code—working with Engineering and Security teams to express requirements as enforceable rules, automated checks, and continuous validation rather than static documents.
• Establish feedback loops between policy and implementation: surface where technical controls diverge from written requirements, identify where policies need to evolve based on infrastructure realities, and ensure that compliance requirements are expressed in terms engineers can act on.
• Design and deploy agentic AI workflows that extend team capacity, using Claude to serve as a virtual GRC analyst to automate evidence analysis, monitor control effectiveness, draft audit responses, interpret policy documents, and handle other tasks that require reasoning over unstructured information.
• Design and maintain integrations connecting GRC tooling with cloud infrastructure, identity management systems, HRIS platforms, ticketing systems, version control, and CI/CD pipelines—working with engineers to implement integrations that enable automated evidence collection and continuous compliance validation.
• Build and lead an AI-forward GRC engineering function as we scale: hiring team members, establishing practices, and defining the technical roadmap for governance and compliance automation at Anthropic.

You may be a good fit if you:

• Have 12+ years of total experience and 3-4+ years of experience managing technical individual contributors or systems-focused teams, with a proven track record of building or scaling small teams (2-5 people) in security, compliance, automation, or operations functions.
• Are a systems thinker first. You understand how complex environments work: how data flows between systems, where integration points exist, what breaks when systems don't talk to each other. Your strength is designing the right architecture and environment for security monitoring, not necessarily implementing it yourself.
• Have 5+ years of experience designing automated workflows, data pipelines, or system integrations, whether through traditional development, low-code platforms, GRC tools, or process automation. We care about your ability to solve integration problems more than your programming language proficiency.
• Have a relentless focus on data integration: you understand how to pull data from multiple sources, normalize it, join it meaningfully, and surface insights. You're comfortable reasoning about messy, inconsistent data and designing systems that handle edge cases gracefully.
• Understand APIs and integration patterns: REST APIs, webhooks, authentication flows, polling vs. push architectures, and can evaluate systems based on how well they expose data and support automation.
• Can work independently with minimal guidance, taking ownership of complex problems from design through implementation while managing ambiguity inherent in early-stage programs.
• Have strong analytical and problem-solving skills with attention to detail necessary for compliance work, balanced with pragmatism about risk-based prioritization in fast-paced environments.

Strong candidates may have:

• Experience designing or implementing AI-powered automation, agentic workflows, or LLM-based tooling in operational contexts.
• Experience with GRC platforms such as ServiceNow GRC, Vanta, Drata, OneTrust, RSA Archer, or similar tools including configuration, customization, and integration capabilities
• Familiarity with scripting languages (Python or similar) for automation tasks, API interactions, and data transformation.
• Prior experience in high-growth startup environments demonstrating ability to build scalable processes and adapt quickly to changing requirements and priorities
• Familiarity with Infrastructure as Code tools (Terraform, CloudFormation, Ansible) and DevSecOps practices including CI/CD pipeline integration and policy-as-code implementations.
• Familiarity with cloud platforms (AWS, GCP, Azure) and an understanding of how compliance-relevant data can be extracted from their APIs and logging systems.

Deadline to apply: None, applications will be received on a rolling basis.

The role:

The Vice President of Biometrics will provide strategic and operational leadership across statistical activities as the company transitions into Phase III clinical trials. This role will be responsible for defining and executing the integrated biometrics strategy, overseeing CRO and vendor partnerships, ensuring data integrity and regulatory readiness, and serving as a key leader on the clinical development team. The ideal candidate brings deep late-stage expertise, strong cross-functional leadership, and a hands-on mindset well suited for a lean, fast-growing biotech organization.

Key responsibilities:

• Provide strategic leadership for biometrics across all clinical development programs, with primary focus on Phase III execution
• Define and implement an integrated biometrics strategy supporting clinical trial design, data quality, statistical analysis, and regulatory submissions
• Serve as a core member of the clinical leadership team, partnering closely with Clinical Operations, Data Management, Regulatory Affairs, Safety, and Medical Affairs
• Lead and oversee CROs and external vendors responsible for biostatistics statistical programming and related biometrics activities.
• Oversee development and review of key deliverables including SAPs, DMPs, CRFs, TFL shells, interim analyses, database locks, and clinical study reports
• Ensure data integrity, statistical rigor, and compliance with GCP, ICH, and global regulatory requirements
• Provide strategic input into study design, endpoint selection, sample size calculations, and adaptive or innovative trial methodologies as appropriate
• Support regulatory interactions and submissions, including briefing documents, responses to health authority questions, and advisory committee preparations
• Establish scalable biometrics processes, standards, and SOPs to support late-stage development and future pipeline growth
• Build, mentor, and lead internal biostatistics capabilities over time, as appropriate to company growth

Required experience & skills:

• Bachelor’s degree or advanced degree, ideally in biostatistics, statistics, mathematics, or a related quantitative discipline
• Minimum of 12 years of progressive experience in biostatistics within the biotechnology or pharmaceutical industry
• Significant experience leading biostatistics activities for Phase III clinical trials and regulatory submissions
• Demonstrated success managing CROs and external vendors in a late-stage development environment
• Proven track record as a strategic biometrics leader, contributing substantively to complex study designs, endpoint development, and statistical strategy across global development programs; able to provide sharp, on-your-feet thinking in real-time discussions with regulators, KOLs, and cross-functional teams, while maintaining a roll-up-your-sleeves approach to engage directly with protocols, analysis plans, and data when needed.
• Strong understanding of global regulatory expectations related to clinical data, statistical analyses, and inspection readiness
• Proven ability to operate strategically while remaining hands-on in a lean organization
• Strong written and verbal communication skills with a collaborative, team-oriented approach
• Ability to thrive in a fast-paced, dynamic environment and remain comfortable with change and ambiguity
• Flexible, proactive, and hands-on mindset with a roll-up-your-sleeves, can-do attitude

Preferred experience & skills:

• Prior experience serving as a functional or biometrics lead in regulatory interactions with FDA and ex-U.S. health authorities
• Experience in cardiovascular, rare disease, or genetically driven conditions
• Background in small or mid-sized biotech companies transitioning into late-stage development
• Experience building or scaling internal biometrics functions and infrastructure
• Familiarity with innovative trial designs and modern statistical methodologies

Base Salary Range: $300K - $375K

Overview of Role

66degrees is seeking a skilled Enterprise Account Executive to empower businesses to shape the future of their work through the power of AI, Data and Cloud. This team member will understand the value of teamwork and love living in the in between of project delivery and managing high trust client relationships. They thrive with autonomy in their position, operating with the highest level of integrity while thinking big and embracing challenges.

Responsibilities

• Work diligently to build the 66degrees’ brand within Google within a designated territory, positioning 66degrees as a trusted, strategic business partner to customers.
• Leverage customer relationships, professional networks and other industry forums to develop a pipeline of opportunities with Enterprise customers in Fortune 1000.
• Accelerate customer adoption of cloud and professional services through targeted education and use engagement points to understand business problems.
• Effectively leverage 66degrees’ internal resources to build and deliver the best solution for the customer.
• Engage partners to develop and execute joint selling approaches to customers.
• Manage numerous accounts concurrently and strategically.
• Provide accurate monthly/quarterly revenue forecasts through disciplined sales and pipeline methodology.
• Collaborate with the marketing department to align current market differentiators and our offerings with digital resources.

• Proactively build and expand on existing customer relationships to drive net new revenue opportunities.
• Prospect on a continual basis to ensure net new business pipeline targets are consistently met.
• Use a consultative/solution selling methodology to translate a customer’s critical business and technology issues into profitable cloud and services opportunities.
• Create and execute a predictable closing plan and work at the executive-level to negotiate and close professional services agreements.

Qualifications

• 5+ years of quota carrying cloud services or professional services sales experience (GCP is preferred). 
• Track record of successfully carrying a seven figure quota; Proven ability of exceeding quota (top 10%-20% of company) in past positions.
• Experience managing the sales cycle from business champion to executive-level decision maker (CXO, VP). 
• Skilled at negotiating and closing services contracts, including proposal and SOW creation.
• Propensity to build strong relationships with customers and partners.
• Effective in orchestrating and managing virtual team members and partners to drive customer engagements.
• Apply a Hunter approach to business development and prospecting.
• Strong knowledge and experience in Amazon Web Services, Microsoft Azure, or Google Cloud Platform; GCP is ideal. 
• Fundamental knowledge of IT architecture preferred.
• Previous consultative selling or solution selling methodology and process training.
• Be highly adaptable and thrive in a changing environment.
• Travel to and within territory as needed. 
• Bachelor’s degree or equivalent work experience. 

This position includes an uncapped commission structure in addition to the base salary listed below: 

⛵️ About Wholesail

Wholesail is an early stage startup that builds software to connect wholesalers and their buyers by automating and digitizing invoicing and payment in the $5 trillion wholesale trade industry. The company’s first product is an electronic invoicing and payment portal for wholesale sellers, which allows them to get paid faster and decrease losses. For buyers, Wholesail automates the accounts payable & expense management process to save them time and money. Wholesail’s initial industry focus is to build a network effect driven payment business in the highly fragmented $1 trillion US food distribution market, in which invoicing and payment is nearly entirely paper-driven today. 

Wholesail was founded by a team of engineers, product managers, and designers whose prior startups were acquired by OpenTable, and the company is well funded with backing from a half dozen VCs and 20+ angel investors including early executives and team members from Stripe, Square, Dropbox, Yelp, OpenTable and Everlane.

Are you fascinated by how people use products, actively seek to understand the “why” behind product decisions, and approach product building as a craft? Are you passionate about working with other experienced engineers who have a passion for their craft? We'd love to have you join our voyage as a founding member of our product engineering team.  

🛠 About the Role

As an early engineer, you’ll build new features and internal APIs to create value for the suppliers and buyers on our network. Your work will skew towards backend development, but you'll end up working up and down the stack and you’ll spend a lot of time with our sales and support team and our customers to figure out the details of the products you craft. Our small product team wears many hats, so you'll get significant exposure to many areas adjacent to engineering: design, marketing, customer success, sales, and all of the functions of an early stage startup.

As a product oriented member of our engineering team, you’ll couple strong technical execution with an active voice in shaping the product through contribution in product conversations and identifying product/technical tradeoffs. You’ll participate in different styles of execution based on the stage of product development – from iterating quickly on an experiment with intentionally scrappy code to building sustainable systems that serve as a foundation for years to come.

Most significantly, you'll be building the company with us. We are early on our voyage and there are vast uncharted seas ahead. We want to work with fellow Wholesailers who care deeply about the process of building an enduring company: from what values we embrace, how we build our teams, decisions about how we grow our business, and everything in between.

🚀  You’d be great a great fit for our voyage if you… 

• Are naturally curious about and have a keen interest in understanding the "why?" by digging into the nuts-and-bolts of how things work as a first principles thinker.
• Think deeply about products – from building empathy for users, to understanding how a product works, how it fits into a complex system, and how it creates business value.
• Obsess about the details of your craft whether it’s designing a new abstraction layer, building an API for a colleague on the frontend team or shipping a pixel perfect feature.
• Quickly build intuition in new domains and are able to articulate product/engineering tradeoffs early on while also pragmatically handling (and minimizing work on) edge cases.
• Estimate and prioritize when faced with different proposed solutions, to help guide the team towards building the most impactful products.
• Strive to quickly deliver value through rapid product validation cycles and have a keen ability to identify quick wins that create value for customers.
• Use data to guide your understanding of user behavior and inform the decisions you make to maximize building value for customers.
• Strive for end-to-end ownership of your work, are proactive with sharing product ideas/opinions, and seek early feedback from other members of your team.
• Build empathy and relationships with strong listening, written, and verbal communication skills – particularly with non-engineering folks such as designers, PMs, support and sales.

🤝 Engineering Culture & Environment

At Wholesail, we started as a team of senior engineers who are passionate about using technology to build products and tools to improve the lives of buyers and sellers in the wholesale industry. Many of us have a background working on technologies used in the relevant food and payments industries, and together with our cross-functional partners, we strive to learn about the problems that our customers in the wholesale industry are facing, so we can work hard to provide solutions for our buyers and sellers.  

Wholesail provides products that help our customers make payments and process orders, which are essential to our customers' business, and therefore we have a strong focus on security, reliability and system performance. We emphasize good engineering practices, and adopt test-driven development and continuous deployment to iterate quickly and confidently. We identify and eliminate or mitigate the impact of single points of failure in our systems. We also genuinely take pride in the craftsmanship of the code we produce, and we love to work with colleagues whose work we respect. Intermixed with all of this is a sense of good humor, and an earnest enjoyment in working together.

Wholesail’s tech stack starts with Java services running in Kubernetes (GKE on Google Cloud Platform), with PostgreSQL as the database. The frontend is a React-Native single page application that is served statically.  The Wholesail platform integrates with third party services and APIs, including Plaid, Stripe, Modern Treasury and QuickBooks, among other systems. Given the financial and accounting nature of the product, the company has invested in extensive testing infrastructure. In addition to more traditional automated testing, we built orchestration that provisions independent copies of the entire service architecture with candidate releases to test the system, end-to-end, before rolling out new changes.

Location: This position can work onsite or hybrid from San Francisco Bay Area. 
Travel: Up to 15%, domestic or international.
Job ID: 1558

The Role: 

We are looking for a Senior Staff Software Architect to lead the design and evolution of our next-generation Network Monitoring Platform. You’ll be part of a cross-functional team whose mission is to lead IonQ on its journey to build the world’s best quantum computers to solve the world’s most complex problems.

In this role, you will own the end-to-end architecture of a high-scale, data-intensive network monitoring platform — from data modeling and ingestion pipelines to cloud-native deployment. You are a hands-on technical leader who writes production code, drives critical architectural decisions, and has deep experience building systems that monitor large fleets of devices at scale. The ideal candidate brings strong Go and/or Rust expertise and thrives at the intersection of systems engineering and distributed data platforms.

Responsibilities:

• Architect cloud-native ingestion and processing pipelines capable of handling telemetry from hundreds of thousands of devices, leveraging streaming platforms and time-series storage at scale.
• Define and own the platform’s unified YANG-based data model, spanning device configuration state, operational telemetry, and topology relationships across heterogeneous network environments, serving as the authoritative schema from which ingestion pipelines, storage structures, and API contracts are derived.
• Write and review production-quality code in Go and/or Rust for performance-critical platform components including collectors, aggregators, and real-time processing engines.
• Define and enforce data partitioning, sharding, and retention strategies to sustain high-volume device event streams while meeting latency and durability requirements.
• Lead the design of cloud-native deployment patterns (Kubernetes, service mesh, autoscaling) to ensure the platform operates reliably at global scale across multi-cloud environments.
• Evaluate and drive adoption of purpose-fit technologies — time-series databases, graph stores, stream processors — with a focus on operational scalability and long-term maintainability.
• Partner with Product and Engineering to translate monitoring requirements into platform capabilities, ensuring architectural decisions are reflected in roadmap milestones and engineering specifications.
• Mentor senior engineers through architecture reviews, coding standards, and hands-on technical guidance, raising the bar for platform quality and engineering practices.

Requirements:

• 12+ years of experience in software or platform architecture, with at least 5 years leading architecture for large-scale, data-intensive distributed systems.
• Substantial experience building and operating device monitoring systems at scale — with direct exposure to telemetry ingestion pipelines, fleet management, and real-time alerting across large device populations.
• Proven hands-on coding ability; production experience with Go and/or Rust is strongly preferred for this role.
• Deep expertise in data modeling for high-volume systems, including schema design, time-series storage (InfluxDB/Timescale), event streaming (Kafka/Kinesis), and graph data models for network topology.
• Solid understanding of cloud-native application design — including containerization, Kubernetes orchestration, microservices, and cloud infrastructure across AWS, GCP, or Azure.

Preferred Qualifications:

• Proficiency in both Go and Rust, with a track record of shipping production services in at least one of these languages.
• Background in network management platforms or network equipment vendors (e.g., Juniper, Cisco, Nokia), with familiarity with telemetry protocols such as gNMI, NETCONF, or SNMP.
• Experience designing multi-tenant SaaS platforms where data isolation, schema evolution, and scalability across customer tiers are first-class concerns.
• Contributions to open-source infrastructure or observability projects, or published technical writing on distributed systems and data engineering topics.
• Familiarity with techniques relevant to high-throughput data collection.

The approximate base salary range for this position is $216,136 - $282,978. The total compensation package includes base, bonus, equity, and a range of benefit options found on our career site.

About the Position
At 6sense, the Post-Sales Solutions Architect is a critical partner to our Strategic and Enterprise Customer Success Management teams, focused exclusively on supporting existing customers throughout their journey with us. This role blends deep technical acumen with strong customer engagement skills to lead architecture design, optimize platform adoption, and ensure our customers realize the full value of their investment.

You'll work directly with our largest and most complex accounts, helping them integrate and scale their use of 6sense by designing innovative solutions, advising on best practices, and serving as a trusted technical advisor post-sale. This is a high-impact, customer-facing role designed to drive retention, value delivery, and long-term growth.

Key Responsibilities

• Partner with Strategic and Enterprise CSMs to lead post-sale technical activities, including product enablement, demos, proof-of-value workshops, and advanced use case development.
• Facilitate architecture design sessions and platform integration planning, aligning customer objectives to 6sense solutions.
• Document business and technical requirements, and clearly communicate the business value of 6sense capabilities to technical and executive stakeholders.
• Serve as a technical liaison between Customer Success, Product, and Delivery teams to ensure a seamless customer experience.
• Lead solution design for multi-product implementations, systems integrations, and data architecture within existing customer environments.
• Proactively identify technical optimization opportunities to improve customer outcomes and platform ROI.
• Contribute feedback to product management and engineering teams, and help evolve internal tooling and processes for customer delivery.
• Build reports and dashboards that help customers track progress, optimize performance, and make data-driven decisions.

Requirements

• 5+ years of experience in a customer-facing technical role, such as Solutions Architect, Technical Account Manager, or Pre/Post-Sales Engineer.
• Deep technical expertise in solution architecture, data integration, and enterprise software.
• Strong interpersonal and communication skills; able to build trust and articulate complex solutions to both technical and business audiences.
• Experience with CRM systems such as Salesforce, Microsoft Dynamics, or SAP.
• Familiarity with marketing automation tools (Marketo, Eloqua, Pardot, Hubspot) and Customer Data Platforms (Adobe Experience Platform, Segment, etc.).
• Experience with ETL/ELT tools (Informatica, DataStage, Netezza) and data visualization tools (Tableau, Looker, Power BI).
• Working knowledge of cloud infrastructure (AWS, Azure, GCP), REST/SOAP APIs, and integration platforms (MuleSoft, Zapier, Dell Boomi).
• Proficiency in programming/scripting languages such as Python, Java, or C++.

Nice to Haves

• Strong problem-solving skills with a customer-first mindset.
• A track record of influencing customer outcomes through consultative engagement.
• Experience supporting SaaS adoption, expansion, or renewal in large-scale enterprise accounts.
• Ability to prioritize and execute across multiple customer projects while managing stakeholder expectations.

Base Salary Range: $139,035.00 - $180,918.00. The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote

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Location: Austin, TX or San Francisco, CA

Solution Architect, AI / Cloudflare Developer Platform 

As a Solution Architect, Cloudflare AI / Developer Platform and a member of the sales team, you will help customers understand the value proposition of the Cloudflare Developer Platform and demonstrate how to effectively build applications with our products. 

Every day as a Solution Architect is different. You will utilize both technical and business skills to advise customers and sales teams, support strategic opportunities, architect innovative solutions, and develop proofs of concept / demonstrations. Your technical knowledge of Cloudflare’s products and system design will be vital to designing solutions that meet our customers’ needs and expectations.

Serving as a trusted technical advisor, Solution Architects guide and enable clients, partners, and teams within Cloudflare on product capabilities, positioning and competitive intelligence. You will form a tight feedback loop with product, product marketing, and technical pre-sales to refine and evolve our products. 

The ideal candidate possesses a consultative mindset, demonstrable success working with customers, and deep, practical knowledge of modern web technologies, cloud architecture, and experience building on a distributed serverless platform. No matter your background, you have natural curiosity and desire to solve problems, achieve goals, and design the most elegant and efficient solutions to address client needs. A successful Solution Architect at Cloudflare is able to act as a trusted advisor for our customers, while balancing the technical and business needs of the role – actively building and regularly presenting technical solutions to varied audiences.

Responsibilities

• Partner with the sales organization to drive revenue, new customers and pipeline of AI and Developer Platform solutions. 
• Lead technical discovery with customers and jointly architect best practice solutions to meet customer needs.
• Collaborate with cross-functional teams including product management, sales, and marketing to drive developer platform revenue and customer adoption.
• Present to strategic customers as an expert of our Developer Platform solutions.
• Align Director and C-Level perceived business and technical value with Cloudflare developer solutions.
• Provide succinct feedback to cross-functional teams to deliver relevant Developer content, use cases, customer stories, and data driven value propositions.

Skill Requirements

• 5+ years of experience selling or supporting technical sales in the cloud computing industry.
• Deep technical expertise across cloud infrastructure and AI/ML — you have built production systems that combine both as a solutions engineer, entrepreneur, or solution architect.
• In-depth knowledge of at least one major public cloud provider (e.g., AWS, GCP, Azure).
• Practical knowledge and experience designing systems. You have built and deployed a production web application either professionally or as a hobbyist and are able to clearly articulate the design and explain the considerations / trade-offs. You are able to hear a clear, non-technical description of an application, ask clarifying questions, and quickly design a high-level, conceptual architecture.
• Software development experience delivering full-stack applications, preferably using modern JavaScript frameworks, a variety of databases, and Serverless tooling. Experience building with modern coding assistants.
• Strong understanding of developer workflows (branching, versioning, CI/CD practices, system integrations).
• Knowledge of key market players/competitors in the cloud computing, AI and storage spaces.
• Up to 30% travel.

Other desirable skills areas include:

• You’ve built something on Cloudflare Workers.
• AWS Solutions Architect or GCP Cloud Architect certifications.
• Providing structured customer feedback to influence product direction.
• Actively stay up-to-date with industry trends and advancements in cloud computing to inform product strategy and roadmap.

Compensation
Compensation may be adjusted depending on work location. 
This role is eligible to earn incentive compensation under Cloudflare’s Sales Compensation Plan. The estimated annual salary range includes the on-target incentive compensation that may be attained in this role under the Sales Compensation Plan.

For Bay Area based hires: Estimated annual salary of 212,000.00 - 292,000.00

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

Available Locations: Austin, Texas

About the Role

The Senior Director of Developer Product Marketing is the strategic lead for how Cloudflare’s developer platform is perceived and adopted in the global market. While our Product Managers build the "what," you own the "why," the "who," and the "how we win." You will lead the team responsible for defining the narrative for Workers, Workers AI, R2, and the broader developer ecosystem, ensuring our story resonates with everyone from solo builders to CTOs at Fortune 500 companies.

In this role, you will move beyond tactical growth loops to focus on the core tenets of Product Marketing: Positioning, Go-To-Market (GTM) Strategy, Market Intelligence, and Sales/Field Readiness. You will be the primary bridge between a highly technical Product organization and our global Sales, Marketing, and Developer Relations teams.

What You Will Do

• Strategic Positioning & Messaging: Define the category-level narrative for the Cloudflare Developer Platform. Create high-impact positioning that differentiates our "Connectivity Cloud" from legacy hyperscalers and niche compute providers.
• Go-to-Market Orchestration: Lead the end-to-end GTM strategy for new products and major feature launches. You will orchestrate the transition from "feature ready" to "market ready," ensuring all internal and external channels are aligned.
• Market & Competitive Intelligence: Act as the "outside-in" voice for the developer organization. Conduct deep competitive analysis and market research to influence the product roadmap and arm our field teams with "how to win" battlecards.
• Field & Sales Enablement: Partner with the Sales and Solutions Engineering leadership to build the playbook for selling to developers and technical buyers. Translate complex technical capabilities into value-based selling tools, demos, and training.
• Customer Insights & Advocacy: Develop a deep understanding of our developer personas. Work with our customers to develop case studies and technical proof points that validate our platform’s impact at scale.
• Cross-Functional Leadership: Serve as a strategic partner to Product Management. While PMs own the product delivery and technical onboarding, you own the market success and the cohesive developer story across the entire Cloudflare portfolio.
• Team Leadership: Recruit and mentor a high-performing team of Product Marketers and Content Strategists, fostering a culture of excellence in storytelling and strategic thinking.

Who You Are

• A Master Strategist: You have a proven track record of taking complex developer technologies and turning them into clear, compelling market narratives. You think in terms of market categories and value props, not just feature lists.
• Technically Credible: You are comfortable "talking shop" with developers and PMs. You understand the nuances of serverless, edge computing, and AI architectures, and you know how to translate those into business outcomes.
• GTM Expert: You have led large-scale launches in the DevOps, Cloud, or Infrastructure space. You know how to align a global organization around a single launch moment.
• Collaborative Leader: You excel at navigating high-growth, PM-led organizations. You know how to provide the "marketing layer" that complements technical product ownership without stepping on toes.
• Data-Driven, Narrative-Led: You use market data and competitive signals to inform your strategy, but you rely on your storytelling instincts to win hearts and minds.

Qualifications

• 10+ years in Product Marketing, with a significant focus on developer-facing tools or infrastructure-as-a-service (IaaS).
• Experience leading PMM teams in a high-velocity, technical environment (e.g., AWS, Google Cloud, Vercel, Stripe).
• Demonstrated ability to influence product roadmaps through market research and competitive intelligence.
• Exceptional writing and presentation skills—you can write the keynote and the technical whitepaper.

Compensation

Compensation may be adjusted depending on work location.

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

Location: Austin, TX; San Francisco, CA

Solution Architect, AI / Cloudflare Developer Platform 

As a Solution Architect, Cloudflare AI / Developer Platform and a member of the sales team, you will help customers understand the value proposition of the Cloudflare Developer Platform and demonstrate how to effectively build applications with our products. 

Every day as a Solution Architect is different. You will utilize both technical and business skills to advise customers and sales teams, support strategic opportunities, architect innovative solutions, and develop proofs of concept / demonstrations. Your technical knowledge of Cloudflare’s products and system design will be vital to designing solutions that meet our customers’ needs and expectations.

Serving as a trusted technical advisor, Solution Architects guide and enable clients, partners, and teams within Cloudflare on product capabilities, positioning and competitive intelligence. You will form a tight feedback loop with product, product marketing, and technical pre-sales to refine and evolve our products. 

The ideal candidate possesses a consultative mindset, demonstrable success working with customers, and deep, practical knowledge of modern web technologies, cloud architecture, and experience building on a distributed serverless platform. No matter your background, you have natural curiosity and desire to solve problems, achieve goals, and design the most elegant and efficient solutions to address client needs. A successful Solution Architect at Cloudflare is able to act as a trusted advisor for our customers, while balancing the technical and business needs of the role – actively building and regularly presenting technical solutions to varied audiences.

Responsibilities

• Partner with the sales organization to drive revenue, new customers and pipeline of AI and Developer Platform solutions. 
• Lead technical discovery with customers and jointly architect best practice solutions to meet customer needs.
• Collaborate with cross-functional teams including product management, sales, and marketing to drive developer platform revenue and customer adoption.
• Present to strategic customers as an expert of our Developer Platform solutions.
• Align Director and C-Level perceived business and technical value with Cloudflare developer solutions.
• Provide succinct feedback to cross-functional teams to deliver relevant Developer content, use cases, customer stories, and data driven value propositions.

Skill Requirements

• 5+ years of experience selling or supporting technical sales in the cloud computing industry.
• Deep technical expertise across cloud infrastructure and AI/ML — you have built production systems that combine both as a solutions engineer, entrepreneur, or solution architect.
• In-depth knowledge of at least one major public cloud provider (e.g., AWS, GCP, Azure).
• Practical knowledge and experience designing systems. You have built and deployed a production web application either professionally or as a hobbyist and are able to clearly articulate the design and explain the considerations / trade-offs. You are able to hear a clear, non-technical description of an application, ask clarifying questions, and quickly design a high-level, conceptual architecture.
• Software development experience delivering full-stack applications, preferably using modern JavaScript frameworks, a variety of databases, and Serverless tooling. Experience building with modern coding assistants.
• Strong understanding of developer workflows (branching, versioning, CI/CD practices, system integrations).
• Knowledge of key market players/competitors in the cloud computing, AI and storage spaces.
• Up to 30% travel.

Other desirable skills areas include:

• You’ve built something on Cloudflare Workers.
• AWS Solutions Architect or GCP Cloud Architect certifications
• Providing structured customer feedback to influence product direction.
• Actively stay up-to-date with industry trends and advancements in cloud computing to inform product strategy and roadmap.

Compensation
Compensation may be adjusted depending on work location. 
This role is eligible to earn incentive compensation under Cloudflare’s Sales Compensation Plan. The estimated annual salary range includes the on-target incentive compensation that may be attained in this role under the Sales Compensation Plan.

For Bay Area based hires: Estimated annual salary of 212,000.00 - 292,000.00

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

Location: Austin, TX or San Francisco, CA

About Cloudflare 

At Cloudflare, our mission is bold yet simple: to help build a better Internet. Our global network handles trillions of requests each month, protecting and accelerating applications without added hardware, software, or code changes. Our Developer Platform, including Workers, Workers AI, R2, KV, Durable Objects, and Pages, empowers developers to build and deploy applications globally, faster than ever before.

About the Team 

The Developer GTM organization is a startup within Cloudflare, driving how we attract, inspire, and grow the next generation of builders. We are redefining what developer acquisition looks like in a world where AI and distributed agents are reshaping the stack. Our mission is to create new pathways for developers to discover Cloudflare, whether through ecosystem partnerships, high impact content, or creative field engagement.

We are builders, storytellers, and connectors united by one goal: to make Cloudflare the most exciting place for developers to build.

About the Role

As the Senior Manager of Solutions Architecture for the AI & Developer Platform, you will lead a team of high-performing technical experts who help customers understand the business value and technical details of Cloudflare’s ecosystem. You will serve as a strategic partner to sales leadership, advising on programs to grow developer revenue and supporting complex strategic opportunities. In this leadership capacity, you will bridge the gap between technical sales and product engineering, ensuring your team effectively acts as the feedback loop that evolves our product offerings.

What you will do

• Strategic Oversight: Develop and execute the long-term technical sales strategy in partnership with regional and country sales leaders to drive pipeline and revenue for the Cloudflare Developer Platform.
• People Management: Directly manage, mentor, and grow a team of Solution Architects, ensuring they successfully serve as trusted technical advisors and regional leads.
• Cross-Functional Collaboration: Serve as the primary liaison with executive leadership, Product Management, and Product Marketing to align goals and deliver data-driven value propositions and customer stories.
• Budget and Resource Allocation: Manage the annual budget and make critical resource allocation decisions to ensure the team is staffed and equipped to meet customer needs and business goals.
• Executive Engagement: Support your team in aligning perceived business and technical value with C-Level executives at strategic customer accounts.
• Product Evolution: Oversee the creation of a succinct feedback loop between the field and internal teams to refine the product roadmap based on customer usage and competitive intelligence.

Who you are

• Technical Sales Leadership: Significant experience leading technical teams, with a background of 7+ years in technical sales of cloud computing, storage, or full-stack engineering.
• Strategic Planning: Proven ability to develop programs that drive sales strategy and pipeline generation in a complex technical environment.
• Deep Technical Expertise: Comprehensive knowledge of modern Web Technologies, Cloud Architecture, AI/ML, and the advantages of Distributed Serverless Platforms.
• System Design Authority: Ability to mentor teams on Systems Design theory and practice for distributed, full-stack applications to solve complex client needs.
• Cross-Functional Leadership: Demonstrated success collaborating with Product, Marketing, and Sales to drive revenue and customer adoption.
• Application Materials: Candidates must submit a resume/CV detailing their experience with team leadership and technical architecture.

Nice-to-Have Skills

• Platform Proficiency: Practical experience where you have built applications or solutions using Cloudflare Workers.
• Industry Certifications: Holding current AWS Solutions Architect or GCP Cloud Architect certifications.
• Developer Workflow Knowledge: Strong understanding of CI/CD practices, versioning, and system integrations to better guide the team on developer workflows.

Compensation
Compensation may be adjusted depending on work location.

For Bay Area based hires: Estimated annual salary of $244,000.00 - $336,000.00

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

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

As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.

You will:

• Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
• Build an internal platform to empower LLM capability discovery.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. 

Ideally you'd have:

• 5+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

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

At Scale AI, we help leading enterprises turn AI from a promising capability into reliable systems that improve real workflows and deliver measurable business value. We are hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment.

This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production. In many cases, the data scientist builds the first usable version of the solution, proves value quickly, and helps drive it into a durable product or platform capability.

The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.

What you’ll do

• Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria
• Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans
• Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems
• Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration
• Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations
• Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement
• Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline
• Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production
• Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities

What we’re looking for

• 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role
• Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact
• Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans
• Strong foundation in statistics, experimentation, causal reasoning, and measurement
• Experience building tools or products, not just analyses — for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications
• Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work
• Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly
• Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives
• High ownership and bias toward shipping in fast-moving environments with incomplete information

Preferred qualifications

• Experience in a forward deployed, solutions, consulting, or other client-facing technical role
• Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products
• Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow
• Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery
• Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems
• Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling
• Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign

What success looks like

Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.

Senior Machine Learning Engineer - Model Evaluations, Public Sector

The Public Sector ML team at Scale deploys advanced AI systems—including LLMs, agentic models, and multimodal pipelines—into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions.

You will:

• Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge–based evaluations.
• Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes.
• Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing.
• Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes.
• Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems.
• Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases.
• Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets.
• Comfortable with light travel (approximately 10%) for customer interaction and team needs.

This role will require an active security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings.
• Strong programming skills in Python; experience with TensorFlow or PyTorch.
• Background in algorithms, data structures, and object-oriented programming.
• Experience with LLM pipelines, simulation environments, or automated evaluation systems.
• Ability to convert research insights into measurable evaluation criteria.

Nice to haves:

• Graduate degree in CS, ML, or AI.
• Cloud experience (AWS, GCP) and model deployment experience.
• Experience with LLM evaluation, CV robustness, or RL validation.
• Knowledge of interpretability, adversarial robustness, or AI safety frameworks.
• Familiarity with ML evaluation frameworks and agentic model design.
• Experience in regulated, classified, or mission-critical ML domains.

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We are looking for a Mission Software Engineering Manager to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.  

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap.
• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation
• 2+ years of prior engineering management or equivalent experience and has managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.

• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• 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
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• 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
• 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
• Understand unique DoD and USG constraints when it comes to technology

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems.

You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment.

What You’ll Do

• Own major full-stack product areas, driving features from design through production deployment.
  
  
• Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness.
  
  
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components.
  
  
• Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences.
  
  
• Deliver experiments and new features quickly, maintaining high quality and tight feedback loops with customers.
  
  
• Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP.
  
  
• Adapt quickly—learning new technologies, frameworks, and tools as needed across the stack.
  
  

Ideal Experience

• 5+ years of full-time engineering experience, post-graduation.
  
  
• Strong experience developing full-stack applications using React, TypeScript, and Python.
  
  
• Experience scaling or shipping products at high-growth startups.
  
  
• Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome).
  
  
• Proficiency with SQL and modern API development.
  
  
• Experience with Kubernetes, containerization, and microservice architectures.
  
  
• Experience working with at least one major cloud provider (AWS, GCP, or Azure).

Scale AI is seeking a highly skilled and motivated Mission Software Engineer to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.   

You will:

• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to >50% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you have:

• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• 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
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• 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
• 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

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)

Scale AI is hiring a highly skilled Senior Software Engineer to help design, build, and operate secure, scalable infrastructure that empowers our employees to do their best work. You’ll join a creative, fast-moving, solutions-oriented group that architects and implements automation across identity and access management, endpoint management, and our broader SaaS stack. The ideal candidate will leverage various in-house and external models/platforms to build applications, slackbots, and dashboards for internal users, and streamline complex workflows through automation. This role will play a major role in elevating the overall velocity of all G&A teams at the organization. 

The Impact You Will Have

• As a full stack engineer (60% BE / 40% FE), you will work with your team to build amazing tools/applications for internal company use as well as external customers/partners
• You will design, develop, test, and support full-stack applications on cloud-native distributed systems
• You will build real-time integrations with SaaS platforms across the organization
• You will build a quality framework/unit tests that ensure product quality, performance, and load and are able to debug/identify system issues
• You will collaborate with the broader teams, engage in engineering council, conduct code reviews, and improve our delivery process
• Collaborate with the IAM team to manage cloud-based identity (Okta) and access controls, ensuring compliance with security policies and standards for internal applications.
• Work heavily cross-functionally to identify areas for corporate technology service improvement and implement self-service solutions.

What We Look For

• 5+ years of related experience with a Bachelor’s degree; or equivalent work experience.
• Proficiency with UI frameworks such as React or Angular and HTML, CSS, Typescript, etc
• Proficiency with backend technologies, including API development, databases, and privacy permissions. Ex. Go, Python, PostgreSQL and GraphQL
• Experience with end-to-end testing and documentation
• Experience developing secure, scalable, and resilient applications on the cloud that handle sensitive data
• Experience with cloud technologies, e.g., AWS, Azure, GCP, Docker, or Kubernetes
• Familiarity with compliance frameworks such as SOC 2, ISO 27001, FedRAMP, and NIST.

About Scale

At Scale AI, 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 abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About the ACE team 

The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. 

About This Role

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Ideally you’d have: 

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally. 

Nice to have:

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax. 
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH 
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.

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 Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders.

You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers.

• Manage the full lifecycle of feature development from requirement definition to deployment on classified networks.
• Direct the orchestration of asynchronous agent fleets to meet mission requirements.
• Lead customer engagements to translate mission needs into technical requirements.
• Own the communication with stakeholders to ensure implementation meets defined acceptance criteria.
• Conduct technical reviews and identify risks within machine learning infrastructure and model serving.
• Drive the platform roadmap by providing technical specifications for Federal product offerings.

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

We are seeking a Senior Security Engineer with a specialty in Detection and Incident Response to join our Security Engineering team. This role sits at the intersection of security operations and software engineering — you won't just investigate incidents, you'll build the systems that detect, contain, and prevent them. You will design and ship high-precision detections across cloud services and enterprise SaaS, develop automation that shortens response timelines, and mature the telemetry pipelines that make it all possible. Your ability to write production-quality code is just as important as your ability to triage an alert.

You will structure investigations, analyze root causes, and clearly communicate the significance of security incidents, their impact, and recommended remediation steps — but you'll also turn those findings into durable engineering improvements: better detections, tighter schemas, and smarter automation.

You will:

• Engineer, test, and deploy detection logic across cloud and enterprise environments, treating detections as software with version control, peer review, and measurable performance.
• Build and maintain incident response automation, runbooks, and tooling that reduce containment timelines without sacrificing developer velocity.
• Mature telemetry pipelines through improved schema design, normalization, enrichment, and quality checks that reduce false positives and increase signal fidelity.
• Perform digital incident investigations to identify and contain potential security breaches.
• Conduct digital forensics and malware analysis to understand attack vectors and adversary methodologies.
• Integrate alerting with messaging and ticketing systems to enable fast, traceable response workflows.
• Partner cross-functionally with IT, security, and engineering teams to harden identity and access patterns, close logging and forensics gaps, and implement maintainable guardrails that scale with the organization.
• Utilize threat intelligence platforms to improve hunting, detection, and response workflows.
• Clearly explain the significance and impact of incidents, providing actionable recommendations to both technical and non-technical stakeholders.

Ideally, you'd have:

• • 5+ years of experience in Detection Engineering, Incident Response, or Security Operations, with a strong emphasis on building and shipping security tooling and automation.
  • Proficiency in at least one programming language (e.g., Python, Go) and comfort writing production-grade code — not just scripts.
  • Hands-on experience designing or improving detection pipelines, SIEM content, and alerting workflows in cloud-native environments.
  • Practical experience with SIEM, EDR, and SOAR tools, with a preference for candidates who have built integrations or extended these platforms programmatically.
  • Strong understanding of modern cyber threats, common attack techniques, and adversary TTPs.
  • Familiarity with digital forensics tools and malware analysis techniques.
  • Experience with cloud-native environments (e.g., AWS, GCP, Azure) and the security telemetry those environments generate.
  • Exposure to threat intelligence platforms and integrating intel into detection and investigation workflows.
  • Strong communication skills, with the ability to translate complex security findings into clear business impact.
  • Relevant security certifications (e.g., GCIH, GCFA, GCIA, CISSP, GDSA) are a plus.

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We’re looking for a hands-on Field Engineering Manager on the front lines leading a team of our field engineering efforts for our federal AI projects, having the opportunity to meaningfully impact millions of dollars in revenue by working closely with our largest public sector customers and ensuring that they become passionate, lifelong Scale customers. This role is ideal for someone who thrives in technical environments, enjoys managing teams while staying close to the code, and wants to work on meaningful problems that impact real world operations across the U.S. government. 

Field Engineers are software engineering generalists who enjoy working with clients directly, taking ambiguous requirements and issues, and quickly designing and building production-grade solutions in close collaboration with the Product, Engineering, and Delivery teams. Field Engineers are experts on Scale's products and codebase, and have general technical knowledge on GenAI systems, APIs, networking, and data engineering. Field Engineers are strong relationship builders, great project managers, and always fun to work with. You’ll play a critical role in delivering technical solutions—all while helping your team grow and execute.

You’ll split your time between technical planning and execution (50%) and people management and team development (50%), leading a team of 6-8 engineers. You’ll work cross-functionally with product, engineering, security, and delivery teams to ensure our engineering efforts meet complex federal compliance, security, and performance needs.

Day to day:

• 50% Field engineering - customer engagement, technical development and delivery 
• 50% Managing a growing team

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of customer facing engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap based on customer needs.
• Work directly with customers to understand their problems and translate those into custom workflows within Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Lead end-to-end technical delivery of custom workflows from scoping to development to testing to implementation
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation.
• 2+ years of prior engineering management or equivalent experience and previously managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. 
• 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.
• Linux experience: Understanding of shell scripting, operating systems, etc.
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 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.
• 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.
• Understand unique DoD and USG constraints when it comes to technology.

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI.

You will:

• Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery.
• Design and implement scheduling primitives to optimize the lifecycle of training jobs.
• Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
• Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability.
• Work closely with Finance and Procurement teams to drive our capacity planning process.
• Participate in our team’s on call process to ensure the availability of our services.
• Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Ideally you'd have:

• 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes).
• Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
• Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling.
• Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling.
• Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
• Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware.
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with distributed training techniques such as DeepSpeed, FSDP, etc.
• Experience with the NVIDIA software and hardware stack (CUDA, NCCL)
• Experience with PyTorch
• Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning

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.

About This Role

Lead applied ML engineering on Scale's Applied ML team, powering data infrastructure for leading agentic LLMs (ChatGPT, Gemini, Llama). You will build scalable multi-agent systems to validate agentic reasoning and behaviors, scale human expertise, and drive research into real-world agent reliability failures despite strong benchmarks, shipping production fixes.

Ideal for exceptional engineers with deep research rigor and a relentless focus on practical, high-impact systems. You will iterate rapidly with data, leverage AI tools to accelerate development, and collaborate tightly across engineering, product, and research.

If you excel at turning frontier agent research into reliable deployed systems, we want to hear from you.

You will:

• Build and deploy multi-agent systems for agentic reasoning validation
• Develop pipelines to detect errors and scale human judgment
• Combine classical ML, LLMs, and multi-agent techniques for reliability
• Lead research into agent failure modes and ship fixes
• Use AI tools to speed prototyping and iteration
• Build data-driven evaluations and deploy rapid improvements
• Integrate systems into Scale's platform

Ideally You’ll Have: 

• PhD or MSc in Computer Science, Mathematics, Statistics, or related field
• 3+ years shipping scaled production ML systems
• Demonstrated real-world impact
• Mastery of PyTorch, TensorFlow, JAX, or scikit-learn
• Deep expertise in agentic LLMs and multi-agent systems
• Strong software engineering and microservices (AWS/GCP)
• Rapid, data-driven iteration
• Proficiency using AI tools to accelerate work
• Strong research depth with practical bias
• Excellent cross-functional communication

Nice to Have: 

• Experience prototyping agent evaluation/reliability systems
• Human-in-the-loop or annotation pipeline work
• Open-source contributions in agents, evaluation, or alignment
• Publications on agent reliability (NeurIPS, ICML, ICLR)

Scale AI is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components.
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have:

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• 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 evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

Scale's Physical AI business unit is dedicated to solving the data bottleneck across Robotics, Autonomous Vehicles, and Computer Vision. This position will be a key contributor in conducting applied research in Physical AI and developing ML pipelines for processing, training, and fine-tuning on data collected by Scale, with a specific focus on optimizing algorithms and pipelines to run efficiently on GPUs in the cloud. In this role, you will have the opportunity to advance research, shape Scale’s offerings, and expand the frontier of data and model evaluation for Physical AI.

The Role 

As an ML Systems Engineer on the Physical AI team, you will design and build platforms for scalable, reliable, and efficient serving of foundation models specifically tailored for physical agents. Our platform powers cutting-edge research and production systems, supporting both internal research discovery and external customer use cases for autonomous vehicles and robotics.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging the gap between Physical AI research and production engineering to accelerate innovation across the company.

You Will: 

• Build & Scale: Maintain fault-tolerant, high-performance systems for serving robotics-related models and foundation models at scale, ensuring low latency for real-time applications.
• Platform Development: Build an internal platform to empower model capability discovery, enabling faster iteration cycles for research teams working on robotics.
• Collaborate: Work closely with Robotics researchers and Computer Vision engineers to integrate and optimize models for production and research environments.
• Design Excellence: Conduct architecture and design reviews to uphold best practices in system scalability, reliability, and security.
• Observability: Develop monitoring and observability solutions to ensure system health and real-time performance tracking of model inference.
• Lead: Own projects end-to-end, from requirements gathering to implementation, in a fast-paced, cross-functional environment.

Ideally, You’d Have: 

• Experience: 4+ years of experience building large-scale, high-performance backend systems, with deep experience in machine learning infrastructure.
• Algorithm Optimization: Deep experience optimizing computer vision and other machine learning algorithms for cloud environments, including GPU-level algorithm optimizations (e.g., CUDA, kernel tuning).
• Programming: Strong skills in one or more systems-level languages (e.g., Python, Go, Rust, C++).
• Systems Fundamentals: Deep understanding of serving and routing fundamentals (e.g., rate limiting, load balancing, compute budgets, concurrency) for data-intensive applications.
• Infrastructure: Experience with containers (Docker), orchestration (Kubernetes), and cloud providers (AWS/GCP).
• IaC: Familiarity with infrastructure as code (e.g., Terraform).
• Mindset: Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to Haves: 

• Exposure to Vision-Language-Action (VLA) models.
• Knowledge of high-performance video processing (e.g., FFmpeg, NVDEC/NVENC) or 3D data handling (point clouds).
• Familiarity with robotics middleware (e.g., ROS/ROS2) or AV data formats.

About Scale AI

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.

Role Overview

As a Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

• Serve as the primary technical point of contact for strategic enterprise accounts
• Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Provide technical training and knowledge transfer to customer teams
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

Scale GP (Scale Generative AI Platform) is an enterprise-grade 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 core infrastructure 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 implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail.

What You’ll Do:

• Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers
• Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs.
• 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

What We’re Looking For:

• 4+ 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)
• Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences

The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and  unique access to massive datasets to deliver improvements to our customers.

Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications.

You will:

• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products
• Build scalable machine learning infrastructure to automate and optimize our ML services
• Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
• Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
• Comfortable with light travel (approximately 10%) for customer interaction and team needs
• This role will require an active security clearance or the ability to obtain a security clearance

Ideally You’d Have:

• Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
• Solid background in algorithms, data structures, and object-oriented programming
• Strong programing skills in Python, experience in Tensorflow or PyTorch

Nice to Haves:

• Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
• Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
• Experience with computer vision, generative AI models, large language models, or agentic systems
• Familiarity with ML evaluation frameworks and agentic model design

About Scale AI

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.

Role Overview

As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Leadership & Collaboration

• Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
• Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 5+ years of software engineering experience with 2+ yrs of  Management experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have: 

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• 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 evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

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:

• 4+ 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)