About role

Roku is seeking a senior-level Identity Engineer to enhance its Zero-Trust architecture, drive standardization initiatives, and optimize its Microsoft-centric identity platform for a geographically distributed workforce. The ideal candidate has hands-on experience in identity and access management (IAM) and securing cloud environments within the Microsoft ecosystem, with deep expertise in Azure Entra ID. Equally important is a strong automation mindset—designing, scripting, and building repeatable workflows. The role also requires the ability to communicate complex technical concepts clearly to both technical and non-technical audiences. 

For New York Only - The estimated annual salary for this position is between $158,000 - $279,000 annually.  Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.

What you'll be doing

• Lead enterprise-wide IAM standardization, including identity lifecycle, access governance, and policy enforcement across global regions.
• Drive automation across IAM to streamline administration and deliver a smoother user experience.
• Support enterprise applications onboarding into Azure Entra ID, including SSO, Conditional Access, and role-based access control (RBAC).
• Enhance privileged access management and implement scalable monitoring, alerting, and auditability solutions to support a secure, geographically distributed workforce.
• Collaborate with IT, Networking, and Security teams to troubleshoot identity-related issues and support global infrastructure initiatives.
• Advance Zero Trust Identity Fabric principles like continuous verification, least-privilege access, and identity-aware policy enforcement across users, devices, workloads, and non-human identities.
• Build identity automation with a DevOps mindset, writing scripts, developing pipelines, and engineering tooling from scratch rather than just configuring them.

We're excited if you have

• 8+ years of hands-on experience with identity and access management and automating cloud technologies, particularly within the Microsoft ecosystem.
• Strong analytical skills and attention to detail, with the ability to troubleshoot complex infrastructure and identity-related issues.
• Excellent communication skills, with the ability to clearly explain technical concepts to both technical and non-technical stakeholders.
• Deep experience with Microsoft Entra ID, including Conditional Access, Identity Governance, and Privileged Identity Management.
• Familiarity with Microsoft 365 services: Exchange Online, Defender, Purview, Sentinel, Intune, and related platforms.
• Automation and scripting skills using PowerShell, Azure CLI, and Microsoft Graph API; working knowledge of Azure services such as Function Apps and Logic Apps.
• Experience in onboarding and managing enterprise applications in Azure Entra ID.
• Advanced knowledge of Azure Single Sign-On (SSO) login methods, including OAuth2, OpenID Connect, and SAML, and their integration with enterprise applications.
• Knowledge of privileged access tools (Azure PIM, CyberArk, etc), secrets management (HashiCorp or Azure Key Vault), and workload identity patterns SPIFEE & SPIRE.
• Familiarity with NHI governance concepts for service accounts and AI agents, and exposure to OPA / Rego or similar policy-as-code frameworks.
• Good to have familiarity with Microsoft Purview for DLP and data classification.
• Strong understanding of multi-factor authentication and FIDO2.
• Familiarity with IT security frameworks and compliance standards.
• Knowledge of logging, monitoring, and alerting practices for identity and access events.
• Basic understanding of email security and DNS.
• Experience with backup and recovery strategies for identity-related services.
• Understanding of Zero Trust Architecture principles.
• Familiarity with Jira and Confluence.
• B.S. in Computer Science, Information Technology, Engineering, or equivalent experience. 

#LI-SR2

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhere—on premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications.

As a Staff Technical Program Manager, you will own the successful delivery of complex, cross-functional efforts. You will partner closely with stakeholders across the organization from Engineering, Product, Product Design, and even Field-facing teams to develop and execute against our overall product vision and business objectives, uncover solutions to technical challenges, and provide data-driven insights that power strategic decision-making.

We are looking to speak to candidates who are based in Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Columbus, Dallas, Miami, Nashville, New York City, Philadelphia, Raleigh, Washington DC, Tysons for our hybrid working model.

Position Expectations

• Leverage technical acumen and analytical skills to drive engineering programs forward and maximize business value delivery
• Recognize patterns in a sea of information and take action accordingly
• Develop a strategic approach to program management that balances agility and process. This involves discerning when to provide direct guidance and when to empower teams by establishing clear frameworks and guidelines for ongoing initiatives
• Build strategic partnerships with Product, Design, and Engineering stakeholders
• Expand knowledge into new domains as called upon
• Act as a mentor to junior TPMs and lead by example
• Embody MongoDB's core values and leadership principles

The right candidate for this role will be

• Experienced with 10+ years of working in an engineering organization leading complex cross-functional technical programs
• Experienced with 5+ years of Software development background
• Able to partner with technical stakeholders in methodically breaking down engineering challenges to deliver against abstract goals
• Able to participate in technical design discussions and summarize trade-offs, outcomes, and next steps
• Skilled at communicating across a diverse set of engineers and stakeholders
• Capable of deep user empathy and adept at balancing product goals and engineering constraints to deliver impactful experiences
• Hyper-organized and capable of coordinating across multiple independent work streams and organizations
• A role model for effective execution practices, driven by an attuned sense of priority and urgency
• Able to leverage their experience in program delivery to influence improvements to our tools, operations, architecture
• Trained in working with project tracking software (e.g. Jira, Rally, MS Project)
• Familiar with MongoDB or a comparable technology

Nice to have!

• Exposed to generative AI and Machine Learning
• Interested in business automation work such as scripting in Python, Google Apps Script and Slack
• Familiar with tools and methodologies for code analysis, refactoring, and automated testing

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: 2263203305

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

Role

We are looking for a Senior Solutions Consultant - AI Security to join our Sales and Go-to-Market team. This is a remote role based in the US, reporting to the Director of Solutions Consulting - AI Security. The Zscaler Sales and Go-to-Market team is a global group of professionals passionate about delighting customers and sharing expertise to drive a secure, cloud-enabled digital future. As a key technical partner, you will demonstrate the power and agility of Zscaler cloud transformation to cement our position as the world leader in cloud security.

What you’ll do (Role Expectations)

• Drive business growth by partnering with Account Executives to deliver compelling product demonstrations and presentations

• Plan, execute, and deliver Proof of Concept (POC) and Proof of Value (POV) projects demonstrating product capabilities and business ROI

• Form lasting customer relationships to ensure success, facilitate smooth onboarding, and cultivate Zscaler product champions

• Act as the voice of the customer by channeling insights to the development team to shape the product roadmap and feature scoping

• Maintain expert-level knowledge of Zscaler offerings, developing business value propositions, and monitoring competitor products

Who You Are (Success Profile)

• You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.

• You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.

• You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.

• You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.

• You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.

What We’re Looking for (Minimum Qualifications)

• Proven experience in a customer-facing technical role such as sales engineering or consulting

• Knowledgeable in Generative AI, cybersecurity, data science or adjacent technical domains

• Excellent communication skills for both technical deep-dives and clear executive briefings

• Proven ability in solving complex technical challenges and effectively managing multiple projects simultaneously

• BSc in Computer Engineering, Computer Science, or equivalent experience

What Will Make You Stand Out (Preferred Qualifications)

• Experience with Python or TypeScript and utilizing REST APIs with tools like cURL and Postman

• AI red teaming experience, agentic system development, or MCP server experience

• Familiarity in major cloud platforms: AWS, Azure, or GCP

#LI-AA5 #LI-Remote

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

Who We Are

About Stripe

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

About the team
As a member of the Partner Solutions Architecture (PSA) team, you will be responsible for providing technical guidance to Stripe’s partners. Our goal is to drive growth through co-solutioning, education and enablement with our partner organisation. The right candidate will be a critical technical liaison to the Stripe Partner Development Manager. This will involve creating comprehensive technical business plans for Partners, including identifying, incubating and bringing to market service/solution offerings built on or with Stripe. A Partner Solution Architect is someone who is intellectually curious, motivated to win, open and entrepreneurial.

What you’ll do

As a member of the team, PSAs build highly consultative trusted relationships with executives and technical decision makers in the customer’s organisation to provide business and technical thought leadership, and become a trusted advisor in solving mission-critical business challenges. We architect business models with them so they can drive new monetization opportunities and growth.

Responsibilities:

• Work with key partners (like AWS) to build out their Stripe capabilities and solutions to grow their business and drive non-linear growth
• Develop and execute enablement plans
• Be at the forefront of technical discussions & solution deep-dives with partners on the value Stripe can provide to their clients
• Engage with CTOs, engineering & other technical leads at key partners to share technology roadmaps, demonstrate the latest innovations, and define a solution strategy to expand the partnership revenue
• Communicate success internally through QBRs, etc.
• Provide oversight, guidance, and assistance during the partners sales process to ensure mutual success in joint opportunities
• Educate the Stripe sales team on key partner solutions and capabilities
• Serve as an advocate for key partners within specific sales regions and identify areas for sales partnership
• Collaborate on technical content (sample code, demos, etc.) to show partners how to implement specific use cases or best practices
• Provide Partner-focused guidance on Stripe’s product through feedback

Who you are

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

Requirements

• 10+ years of experience in a similar customer-facing engineering role such as solution consultant, solutions architect, sales engineer, for a global software enterprise.
• 5+ years of experience of working on hyperscaler platforms (like AWS, Azure, GCP)
• Experience co-selling and co-solutioning with go-to-market partners.
• Executive engagement skills and presence, with an ability to establish strong relationships with key decision makers and build credibility at all levels.
• Effective group-facilitation skills and confidence in proposing and leading customer meetings to gain strategic footing and pursue opportunities.
• Thorough understanding of the software development lifecycle and API architecture.
• Outstanding spoken and written communication skills, presentation skills, and confidence in explaining complex concepts to both technical and non-technical audiences.
• Ability to learn Stripe solutions such as Payments, Billing, Connect, and more.
• Ability to understand how a wide variety of applications such as ERP, CRM, Billing, Tax and legacy systems interact with each other in an enterprise technology ecosystem. 
• Strong organisational and time management skills and the ability to juggle competing priorities while working with multiple strategic opportunities and customers.
• Strategic and creative thinker who can proactively identify challenges and maintain a positive approach when facing difficult obstacles.
• Background and experience with Crypto technologies and Stablecoins will be a plus.

About Stripe

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

About the team

At its core, Stripe is a treasury company, and the Treasury Finance team is key to building the Global Payments and Treasury Network (GPTN). We collaborate closely with product, engineering, sales, and finance teams to create innovative solutions that enhance Stripe’s financial capabilities. As part of Treasury Finance’s AI and Quantitative Analytics team, you’ll work at the intersection of finance, artificial intelligence, and product development, building autonomous agents and intelligent solutions that enhance treasury capabilities and enable us to better serve and scale with the global economy. 

What you’ll do

Within Treasury Finance AI and Quantitative Analytics, you’ll leverage your finance, artificial intelligence (AI) and technical expertise to  build intelligent solutions that enhance Stripe’s treasury capabilities. You’ll develop AI-powered tools and models, autonomous agents, and data products that automate complex workflows and provide actionable insights. Working at the intersection of artificial intelligence, finance, and product development, you'll collaborate with engineering and finance teams to deploy cutting-edge AI applications that scale with Stripe's growth and support our mission of increasing the GDP of the internet. 

You will:

• Apply your treasury and finance domain expertise to identify high-impact opportunities where AI can solve complex liquidity, financial risk management, and capital markets challenges
• Build AI-powered tools and artificial intelligence solutions to automate treasury workflows, enhance risk management, and scale our operations
• Design and deploy autonomous AI agents using frameworks like LangChain and LangGraph that can reason, plan, and execute complex multi-step problems and enhance decision-making processes
• Ship interactive data products and self-service analytics tools using Python frameworks (Streamlit, Dash, Gradio) that provide real-time insights and actionable intelligence
• Work across Treasury Finance and partner teams to scope AI-driven solutions that allow us to optimize and scale our most complex, data-driven financial workflows 
• Explore and prototype cutting-edge AI applications to address emerging treasury challenges

Who you are

We’re looking for a technical problem-solver with treasury and finance expertise who’s excited about leveraging artificial intelligence and who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• Bachelor’s degree in finance, mathematics, computer science, engineering or a related field with 5+ years of work experience in software development, data science, or treasury/finance roles 
• Working familiarity with financial risk and capital markets concepts
• Proficiency in Python and experience with AI/ML frameworks including PyTorch and TensorFlow
• Experience with Large Language Model (LLM) frameworks such as LangChain, LangGraph, or similar tools for building AI applications and agentic systems
• Solid understanding of AI fundamentals, including deep learning, natural language processing, and generative AI
• Results-oriented, with a focus on delivering impact in a fast-paced environment 
• Excellent communication skills for collaborating with product, engineering, and finance teams
• Highly organized, with attention to detail and the ability to manage tight deadlines

Nice to have

• • Familiarity with the payments industry and fintech landscape
  • Experience with Databricks and cloud platforms (AWS, GCP, Azure) 
  • Software engineering experience in Ruby

We are seeking a Senior Sourcing Lead – Cloud & AI Inference to join our Global Procurement team. This role will serve as a strategic leader in driving cloud and AI infrastructure sourcing initiatives both across the US and globally, with a primary focus on optimizing third-party cloud spend, structuring hyperscaler commercial agreements, and enabling scalable growth of our cloud and AI footprint. As a senior member of the team, you will not only lead complex sourcing strategies, but also provide oversight, coaching, and guidance to sourcing managers and buyers on the US team.

This role requires deep domain expertise in cloud commercial models, including hyperscaler enterprise agreements (AWS, GCP, Azure), committed-use and reserved capacity pricing, and AI inference procurement.

You will partner directly with senior stakeholders, technology leaders, platform engineering, and finance teams to ensure we are extracting maximum value from our cloud investments, building cost transparency, and driving measurable business impact in our fastest-growing technology spend category.

Key Responsibilities

• Own and execute the cloud and AI inference category strategy across our organization (both within trading infrastructure and enterprise-wide).

• Lead negotiations for high-value and complex hyperscaler agreements (Enterprise Discount Programs, Committed-Use Discounts, Private Pricing Agreements), ensuring best-in-class commercial outcomes and risk mitigation.

• Drive measurable cost optimization initiatives across cloud and AI inference spend through FinOps discipline, multi-cloud benchmarking, and consumption analytics, while balancing speed, scalability, and innovation.

• Influence senior stakeholders (up to executive leadership) to align on cloud sourcing strategies, architectural trade-offs, and commercial business cases.

• Establish and strengthen key vendor relationships with hyperscalers and emerging AI infrastructure providers to maximize long-term value and innovation.

• Monitor cloud market trends, hyperscaler pricing benchmarks, and supplier performance to proactively identify opportunities for savings and improvement.

• Represent Procurement as a trusted advisor to technology and business leadership on all cloud and AI inference investment decisions.

Required Experience

• 10+ years of sourcing/procurement experience, with significant depth in cloud or hyperscaler procurement.

• Demonstrated success leading large-scale cloud negotiations and delivering multimillion-dollar savings or cost avoidance.

• Experience building and executing cloud category strategies at an enterprise level.

• Proven ability to influence and collaborate with senior technology executives, including Platform Engineering and CTO-level stakeholders.

Required Skills

• Excellent negotiation, analytical, and financial acumen, with deep understanding of cloud pricing mechanics.

• Strong leadership presence with ability to communicate complex cloud sourcing strategies clearly to stakeholders at all levels.

• Strategic thinker with demonstrated ability to balance cost optimization, innovation, and architectural flexibility.

• Expertise in leveraging cloud consumption data and cost models to drive sourcing strategy creation.

• Ability to thrive in a fast-paced, high-impact environment with competing priorities.

Preferred Qualifications

• Bachelor's degree in Business, Supply Chain, Finance, Computer Science, or related field.

• Experience within financial services, trading, or other complex tech-focused industries.

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.

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

Code and Theory is seeking a senior cloud engineer who wants to own the full technical lifecycle of enterprise client deployments — from assessing a client's existing infrastructure and designing the integration architecture, to provisioning the environment and keeping it running in production. This is a hands-on role that also requires real client engagement: you will sit in technical working sessions, work directly with client DevOps teams, and be the person who translates security and compliance requirements into concrete infrastructure decisions.

You will be working on a platform that connects our AI product to enterprise marketing environments across different cloud providers. Each client brings its own infrastructure, data stack, and security perimeter. Your job is to figure out how to connect to it, build the integration reliably, and hand it off in a state that can be operated and maintained over time.

WHAT YOU'LL DO

• Assess each client's cloud infrastructure, data stack, and security perimeter before any build starts — translate findings into a concrete integration plan
• Design and provision client environments using Terraform — networking, IAM, container orchestration, managed storage, and secrets management across GCP, AWS, or Azure depending on the client
• Deploy and operate LLM inference pods in client cloud environments — managing API integration, rate limits, latency, and failure handling without needing a data scientist in the room
• Build and maintain integration layers that connect client data sources to the AI layer — you own the plumbing that makes inference useful; the data science team owns what runs on top of it
• Deploy and maintain containerized workloads via Helm — orchestration, ETL workers, and AI inference pods running inside the client's cloud perimeter
• Own data pipeline deployments end to end — scheduling, pagination, retry logic, and rate-limit management against client API gateways
• Manage distributed ETL jobs at scale — JSON flattening, schema enforcement, and structured output delivery
• Enforce data residency requirements — raw data stays inside the client's environment, only structured output leaves to our shared infrastructure
• Serve as the primary technical contact for each client's DevOps and infrastructure teams throughout the engagement
• Lead technical working sessions with client teams — validate configurations, confirm IAM and credential models, review cluster specs before deployment
• Triage and resolve pipeline and infrastructure failures across multiple client environments simultaneously
• Implement container security standards — non-root execution, read-only filesystems, startup integrity hashes, tamper protection
• Mentor junior and mid-level engineers and contribute implementation patterns to the shared playbook after every client engagement

WHAT YOU'LL NEED

• 6+ years of cloud engineering experience — production experience on at least two of GCP, AWS, or Azure, and willing to operate across all three depending on client environment
• Deep Terraform experience — you have provisioned multi-environment, multi-tenant production infrastructure from scratch, not just applied existing configurations
• Comfortable with Kubernetes and Helm in production — deploying, debugging, scaling, and securing containerized workloads, not just running them
• Have run data pipelines in production — you know what breaks, how to recover, and how to build retry and backoff logic that actually holds up
• Hands-on experience with distributed processing at scale — not just theoretical knowledge
• Enterprise API integration experience — OAuth 2.0, API key management, rate limiting, API gateways — end to end
• Solid security fundamentals — container hardening, credential management, and data residency enforcement in environments where it actually matters
• Have worked directly with client or customer engineering teams — comfortable leading technical conversations with enterprise DevOps and infrastructure teams, not just supporting them
• You write things down — runbooks, integration notes, playbook contributions. The next engineer should be able to operate what you built
• Hands-on experience integrating LLM APIs (Anthropic, OpenAI, or equivalent) into production pipelines — not as an end user, but wiring inference into systems that run at scale across real client environments

NICE TO HAVE

• Experience with:
  • LLM inference infrastructure
  • Marketing technology stacks (DAM, CDP, CRM)
  • Multi-tenant client environments
• A cloud certification (AWS Solutions Architect, GCP Professional Cloud Architect, or Azure equivalent)
• Agency, consultancy, or product company background serving multiple enterprise clients simultaneously

ABOUT US

Born in 2001, Code and Theory is a digital-first creative agency that sits at the center of creativity and technology. We pride ourselves on not only solving consumer and business problems, but also helping to establish new capabilities for our clients. With a global client roster of Fortune 100s and start-ups alike, we crave the hardest problems to solve. We have teams distributed across North America, South America, Europe, and Asia. The Code and Theory global network of agencies is growing and includes Kettle, Instrument, Left Field Labs, Create Group, Current, and TrueLogic.

Striving never to be pigeonholed, we work across every major category: from tech to CPG, financial services to travel & hospitality, government and education to media and publishing. We value the collaboration with our client partners, including but not limited to Adidas, Amazon, Con Edison, Diageo, EY, J.P. Morgan Chase, Lenovo, Marriott, Mars, Microsoft, Thomson Reuters, and TikTok.

The Code and Theory network is comprised of nearly 2,000 people with 50% engineers and 50% creative talent. We’re always on the lookout for smart, driven, and forward-thinking people to join our team.

The target range of base compensation for this role is $110,000 - $150,000. Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, and location.

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 Security Products organization at CoreWeave builds the identity, encryption, and self-managed security integrations that protect AI workloads and data across our cloud platform. If you are passionate about building foundational security primitives that enable enterprises and the top AI labs in the world to deploy regulated and security‑sensitive workloads at extreme scale, this is the team to join!

About the role

CoreWeave is seeking a Staff or Principal Engineer for our Security Products team to lead the technical direction and implementation of encryption and key lifecycle management  In this role, you’ll design and evolve the key lifecycle management, encryption control planes, algorithm/library selection, and systems integrations that allow CoreWeave customers to deploy sensitive, high security AI workloads and data. You’ll partner closely with teams across CoreWeave to develop customer-driven cryptography technology. Your day‑to‑day will blend hands‑on system design and coding with cross‑team technical leadership, design reviews, and roadmap shaping for Security Products.

In this role, you will:

• Lead the design and evolution of encryption and key lifecycle management products.
• Manage encryption and cryptography technology development for services within our Cloud Platform, particularly those for high security and highly regulated customers.
• Design and build deep integrations between our Cloud Platform and external key sources (eg, HashiCorp Vault, AWS KMS, HSMs).
• Collaborate with other product engineering teams to support the safe use of multicloud key management technology.
• Partner with IAM to define unified authorization patterns and policy models for key management APIs with consistent semantics across the resource hierarchy.
• Establish SLIs / SLOs for Remote Key Encryption (RKE) and related services, including availability, latency, and durability guarantees for key retrieval and encryption operations.
• Partner with the Security Engineering team on threat modeling and corporate strategy to enable the most sensitive AI workloads in the world to be deployed on CoreWeave's infrastructure.
• Author and review detailed technical designs and RFCs for new RKE capabilities, mentor other engineers on the team, and provide technical leadership across Security Products and adjacent organizations.

Who You Are

• 8+ years of experience building and operating distributed backend systems in production, including ownership of reliability and security outcomes for critical services.
• Deep experience with encryption at rest and key management systems, including envelope encryption patterns, key hierarchies and secure key lifecycle management.
• Hands-on experience integrating with at least one major KMS or secrets manager (e.g., AWS KMS, HashiCorp Vault, Azure Key Vault, GCP KMS, HSMs), including designing APIs and workflows around those systems.
• Strong proficiency in a systems programming language such as Go (preferred) or Rust, with experience building networked services (gRPC / REST) in a Linux / Kubernetes environment.
• Solid understanding of applied cryptography concepts relevant to data‑at‑rest protection (AES‑GCM/CTR, key wrapping, KDFs, randomness requirements, envelope encryption, and key separation) with the ability to reason about threat models and failure modes with Security partners.
• Experience designing and operating multi‑tenant services with strong isolation and authorization semantics across customers and internal tenants.
• Demonstrated track record of leading cross‑team technical initiatives, driving projects from problem statement through rollout, alignment, and operational readiness.
• Strong operational experience defining SLIs / SLOs, building dashboards and alerts, and partnering with SRE / Production Engineering on incident response and post‑incident improvement.
• Excellent written and verbal communication skills with the ability to produce clear, opinionated design docs that influence Senior Engineers, PMs, and Security stakeholders through context setting and sound technical judgment

Preferred (if applicable)

• Prior experience designing or implementing remote or externalized key management for cloud storage, databases, or filesystems (e.g., BYOK/BYOKMS, customer‑managed keys, envelope encryption for S3‑like object storage).
• Experience with hardware‑backed key management (HSMs) and cryptographic compliance regimes (FIPS 140‑2/3, PCI, HIPAA, FedRAMP Moderate+, or similar) and how they shape system design.
• Familiarity with IAM policy models (RBAC / ABAC, OpenFGA, OPA/Rego, etc.) and how to integrate fine‑grained authorization into security‑sensitive APIs.
• Experience extending encryption and key management across multiple storage domains (object storage, block/file storage, databases, control plane state like etcd) in a coherent way.
• Background working in security‑sensitive or regulated environments where auditability, segregation of duties, and key custody requirements are critical.
• Contributions to open source cryptography, security tooling, or KMS/client libraries.
• Previous US/NATO federal cryptographic security experience is ideal but not necessary. 

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You care deeply about getting the cryptographic and operational details right, and you’re comfortable saying “no” to shortcuts that weaken security or key custody guarantees.
• You’re excited by the challenge of building foundational security primitives that other product teams and large enterprises will build on for years.
• You enjoy working at the intersection between Platform, Storage, IAM, and Security Engineering, and you can translate between those domains without losing the plot.
• You’re skilled at turning complex requirements for highly regulated customers into simple, reliable, well‑documented APIs and workflows.
• You’re comfortable operating in a fast‑moving environment, iterating quickly while still holding a high bar for design review, testing, and safe rollout of security‑sensitive changes.

The base salary range for this role is $206,000 to $303,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

About Role

Clockwork is seeking a sales-savvy individual with extensive technical expertise in AI networking to fill our Senior Solutions Engineer position. Do you thrive in a fast-paced, dynamic environment? Utilize your networking expertise, systems engineering background, and consultative skills to partner with our sales team throughout the entire customer journey—from understanding requirements and delivering compelling technical presentations and demos to conducting proof-of-concept (PoC) evaluations and overseeing complex software deployments.

What you will do

• Collaborate closely with customers to understand their unique business needs and create, prototype, and deploy tailored solutions that align with their requirements.
• Lead proof of concept evaluations to showcase the value of Clockwork's solutions within customer environments.
• Provide technical leadership during customer meetings, presentations, and workshops, addressing any technical queries or concerns that arise.
• Work closely with Clockwork's sales team to complete PoC evaluations and close deals.
• Collaborate with product and engineering teams, and identify opportunities for product enhancement.
• Offer valuable insights on product features, functionality, and performance, contributing to discussions about product strategy and architecture.
• Stay abreast of the latest developments and trends in AI networking, Kubernetes, and cloud computing, sharing your thought leadership with customers and internal stakeholders.
• Represent Clockwork at conferences and industry events, with occasional travel as required.

Experience/skills you bring to the position

• 5+ years in a solutions architect or engineering role, preferably within cloud or AI infrastructure domains.
• Previous pre-sales experience, including POCs, with client stakeholders, including senior technical staff and management.
• Hands-on experience with cloud platforms (AWS, GCP, Azure, OCI).
• Strong understanding of Kubernetes and container orchestration.
• Familiarity with GPU infrastructure and related technologies.
• Extensive knowledge of networking protocols.
• Excellent communication and relationship-building abilities, with a customer-centric mindset.
• Demonstrated ability to troubleshoot complex technical issues and provide effective solutions.
• A degree in computer science, electrical engineering or related field.
• Proficiency with Python, SQL, and Linux (Golang, C, C++, and Java are a plus).

Compensation for this position will vary based on the skills and experience you bring, as well as internal equity considerations. For candidates hired at the posted level, the expected base salary range is $170,000 - $250,000. In addition to cash compensation, this role is eligible to participate in the company’s equity program, which may include stock options granted in accordance with the company’s equity plan and subject to approval and applicable vesting schedules.

Enjoy

• Challenging projects.
• Competitive compensation.
• A great benefits package.
• A friendly and inclusive workplace culture.
• Catered lunches.

Who are we hiring?  
The Incident Response Analyst is responsible for monitoring, investigating, and responding to security alerts and incidents across the organization. This role partners with internal and external teams to contain threats, remediate vulnerabilities, and restore impacted systems in a timely manner. The Incident Response Analyst also supports incident investigations, documents findings, and helps strengthen the organization’s overall security posture. The ideal candidate is an analytical problem solver who communicates effectively and thrives in a collaborative, fast-paced environment. 

What will you do? 

• Responsible for carrying out daily security monitoring and response procedures. 
• Perform initial incident assessment, evidence gathering, and triage.
• Escalate incidents and participate in or lead remediation efforts.
• Investigate and remediate security events occurring in email, workstations, firewall and other platforms.
• Document and report steps taken to resolve security events using information security runbooks and templates.
• Provide feedback and recommendations for improvement of security controls and response procedures.
• Assist with expanding MDR/SIEM capabilities, including log coverage, alert development, and process improvements.
• Report weekly metrics to the Information Security Leadership.
• Collaborate with the Technology, People Practices, and Legal and Business Affairs departments to build a more secure MSG.
• Participate in On-Call rotation to remediate alerts/incidents outside regular business hours.
• Assist with managing, analyzing, and remediating phishing emails within our security platform.
• Other information security projects/duties as assigned.  

What do you need to succeed? 

• 2-4 years of related experience    
• Bachelor’s degree, or equivalent combination of education and experience
• 1-2 years of experience in information security and/or digital forensics involving investigating and remediating cyber events.
• Comprehend current cyber security threats such as spear-phishing campaigns, business email compromises, and back-door Trojan malware.
• Experience with Endpoint Detection and Response tools such as Carbon Black, SentinelOne and Microsoft Defender.
• Has a basic knowledge of Windows, Mac, and Linux operating systems. iOS and Android mobile devices.
• Must have experience dealing with confidential information and tact when working on sensitive investigations
• Has a basic knowledge of traditional networking (TCP/IP, DNS, DHCP, etc.) and cloud infrastructure, such as AWS, GCP, and Azure.
• Able to document detailed investigations, remediations, and procedure changes.
• Communicates effectively with peers, partner teams, and management.
• Enjoys thinking analytically and solving problems individually and as a team.
• Possesses a passion for learning all things, information security and incident response. 

Application Requirements  

• All applicants must submit a cover letter addressing the following question for consideration:
  • How do you demonstrate initiative and independent problem-solving in technical or cybersecurity-related work?
  • Applications without a cover letter will not be considered. 

Special Requirements  

•  Participates in On-Call rotation to ensure security incident response coverage is available 24/7/365 
• Possible travel of up to 10% if onsite presence is required at the company’s other locations.  

#LI-Onsite 

Available Locations: NYC

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 NYC based hires: Estimated annual salary of $185,000 - $254,000

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

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking a VP-level AI/ML Engineer to deploy AI solutions at enterprise scale, with a strong emphasis on Large Language Model (LLM) applications and modern MLOps & AIOps practices. This role sits at the intersection of data science and software engineering, reporting to the manager of the IT Application Development and Support team and working closely with the Chief Artificial Intelligence Officer, transforming innovative AI prototypes into robust, scalable production systems. The AI/ML Engineer will lead the deployment of high-impact AI capabilities (e.g., generative AI systems, personalization engines, automation tools) and ensure scalable AI platforms that deliver real-world value. The role also includes designing, constructing, and maintaining the Bank’s AIOps solution, with Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Production Architecture & AIOps

• Establish and enforce architecture standards for production AI systems, including data pipelines, model serving infrastructure, and real-time inference services.
• Implement AIOps/MLOps pipelines for CI/CD of ML models, model governance, monitoring, and lifecycle management.
• Design and maintain scalable software applications with integrated AI/ML capabilities.
• Develop software architecture and design patterns to ensure performance and scalability.
• Write clean, maintainable code in general-purpose programming languages (Python, Java, C, C++, Go).
• Implement and manage data pipelines for preprocessing and transforming data for AI/ML models.
• Integrate AI/ML models into production environments and optimize for reliability and scalability.
• Apply Site Reliability Engineering (SRE) principles and implement monitoring and alerting solutions.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay current with advancements in software engineering and AI/ML technologies.
• Adhere to agile and lean software development best practices.
• Thoroughly document all developed models and processes according to relevant policies and standards.
• Support the production environment by either resolving technical or functional issues, in line with the procedures defined by the Bank.

Cross-Functional Collaboration

• Partner with data scientists, AI scientists, product managers, data engineers, DevOps, and business stakeholders to operationalize AI algorithms.
• Mentor or train teams and coordinate between research-oriented AI scientists and engineering teams to continuously improve models with production feedback.

Scaling & Performance

• Ensure AI solutions perform at scale, handling thousands of daily inferences with low latency and high reliability.
• Optimize model serving using techniques like model compression, caching, and hardware acceleration.

Implement robust monitoring and alerting for model performance to detect and address degradation (e.g., drift, latency issues).

Qualifications & Skills:

• 6+ years of experience
• Master’s or PhD in a relevant field (Computer Science, Software Engineering,  Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML
• LLM & GenAI Mastery: Expert in building and deploying LLM-based applications using RAG, prompt engineering, and vector databases. Skilled in LLMOps tools (LangChain, LlamaIndex) and fine-tuning models for enterprise use, including agent-based architectures.
• MLOps & Cloud Infrastructure: Proficient in cloud ML platforms (AWS, GCP, Azure) and MLOps workflows. Uses Docker, Kubernetes, and IaC tools (Terraform, CloudFormation) for scalable deployments. Experienced in CI/CD, real-time inference, GPU optimization, and ML observability (Prometheus, Grafana, MLflow).
• Full-Stack Development: Capable of building end-to-end AI solutions, from front-end (React) to back-end APIs (Flask, FastAPI, Node.js). Skilled in integrating ML models with databases (SQL, NoSQL) and delivering seamless user experiences through robust software engineering.
• Proficient in Python (pandas, scikit-learn), deep learning (PyTorch/TensorFlow/Keras), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• Experienced with Snowflake-native ML (Snowpark Python, UDFs/UDTFs, Tasks/Streams).
• Competent in data engineering (SQL, ETL/pipelines, Spark/PySpark) and handling large structured/unstructured datasets.
• Strong understanding of AI/ML algorithms, application architecture, and design patterns.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications & Skills

• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on experience with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions, and feature management/registry tooling.
• Familiarity with fairness toolkits, XAI frameworks, and preparing models for validation, audit, or regulatory exams.
• Knowledge of SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment.
• Excellent written and verbal communication skills.
• Strong listening and teaching abilities.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Quick learner of new technologies.
• Self-directed with strong technology and communication skills.
• Ability to synthesize multiple sources of information and understand the broader operational context of the Bank.
• Collaborative team player with a practical and creative approach in a dynamic work environment.
• Ability to handle ambiguity, multitask, and adapt quickly to changing priorities.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type 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.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank is seeking a VP-level Applied AI & Machine Learning Scientist to design, build, and validate production-grade AI/ML and Generative AI solutions in a highly regulated banking environment. This role focuses on high-impact use cases—fraud detection, AML alert optimization, AI-assisted credit memo generation for underwriting decision support, contact center AI assistant/copilots, and personalization for treasury/commercial clients—delivered with rigorous governance, explainability, fairness testing, privacy-by-design, cybersecurity, and model lifecycle controls aligned to SR 11-7 and MCB’s Trustworthy & Responsible AI Principles. The role emphasizes Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Applied AI/ML development:

• Design and implement models for fraud detection, AML alert scoring/triage, AI-generated credit memo drafting and underwriting decision support, contact center AI assistants, and personalization for commercial/treasury use cases.
• Leverage modern methods: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings and vector databases, transformers, boosting, anomaly/outlier detection, and classical ML.
• Embed explainability (e.g., SHAP, interpretable scorecards/monotonic models) and conduct pre-/post-deployment bias testing with documented remediation.

Model validation, documentation & governance (SR 11‑7):

• Produce audit-ready documentation (methodology, assumptions, data lineage, limitations, testing) and register models in the inventory with owners/materiality.
• Facilitate independent validation/effective challenge; obtain required approvals before deployment; maintain change management and periodic review cadence.
• Define monitoring, drift thresholds, retraining triggers, and safe rollback/kill-switch procedures; maintain human-in-the-loop checkpoints for high-impact decisions.

Productionization & MLOps on Snowflake

• Package, deploy, and operate models via CI/CD, containerization, and model registry; instrument KPIs/KRIs and alerting dashboards. Operate models natively on Snowflake using Snowpark Python, UDFs/UDTFs, Tasks/Streams, and secure external access where required.
• Partner with Engineering to integrate models via secure APIs/batch; ensure scalability, resiliency, and observability in cloud/on‑prem (e.g., Snowflake, Azure ML, Databricks).

Regulatory, privacy, and cybersecurity alignment:

• Design for ECOA/Reg B (adverse action specificity), UDAAP, FCRA, GLBA privacy, and NYDFS 23 NYCRR 500 cybersecurity requirements.
• Apply privacy-by-design (data minimization, purpose limitation, retention), strong access controls/segregation, and secure SDLC/red teaming for GenAI stacks.

Third‑party AI & data stewardship:

• Support due diligence, testing, and ongoing monitoring of vendor AI/data providers per SR 23‑4; evaluate conceptual soundness, fairness, and security.
• Negotiate/verify contractual controls (no vendor training on MCB/NPI, subprocessors disclosure, audit rights, exit/portability).
• Ensure AEDT compliance (NYC Local Law 144) for any HR-related AI tools.

Cross‑functional partnership:

• Collaborate with Model Risk, Compliance/Legal, Cyber/IT, Data Privacy, Internal Audit, and business owners to meet objectives while staying within risk appetite.
• Communicate complex results, risks, and limitations clearly to technical and non‑technical stakeholders (management committees, examiners).

Innovation, coaching, and best practices:

• Evaluate emerging ML/GenAI methods, LLM evaluation techniques, Snowflake‑native capabilities (e.g., vector search, orchestration), and governance tooling; lead POCs within established control gates.
• Mentor junior staff; promote responsible AI practices, documentation standards, and reproducibility.

Qualifications & Skills:

• 6+ years of relevant work experience.
• Expertise in Python (pandas, scikit‑learn), deep learning (PyTorch/TensorFlow), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• MLOps proficiency with CI/CD, containerization (Docker), registries, and observability; cloud ML (Snowflakes-native ML, Azure ML or Databricks preferred).
• Snowflake‑native ML proficiency: Snowpark Python, UDFs/UDTFs, Tasks/Streams; ability to build and operate ML workflows inside Snowflake.
• Data engineering competency (SQL, ETL/pipelines, Spark/PySpark); ability to work with structured/unstructured data.
• Explainability (e.g., SHAP) and fairness testing; ability to produce interpretable reason codes for ECOA/Reg B adverse actions as applicable.
• Strong grasp of SR 11‑7 lifecycle, model documentation, and operational monitoring within three lines of defense governance.
• Excellent communication; ability to translate technical detail to business/risk stakeholders and drive decisions.
• Curiosity and problem‑solving mindset; ability to balance innovation with disciplined risk management.

Preferred Qualifications & Skills

• Master’s or PhD in a relevant field (Computer Science, Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML, NLP, or model interpretability.
• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions; experience with feature management/registry tooling a plus. model registry and pipeline orchestration; Kubernetes a plus.
• RAG architectures, vector databases, prompt engineering, and LLM evaluation (accuracy, hallucination, safety).
• Fairness toolkits and XAI frameworks; experience preparing models for validation, audit, or regulatory exam discussions.
• Familiarity with SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment
• Must have excellent written and verbal communication skills
• Must be a good listener and good teacher
• Demonstrate analytical, troubleshooting and problem-solving skills
• The ability to learn new technologies quickly
• Self-directed individual with technology and communication skills.
• Ability to take in multiple sources of information with an understanding of the bigger picture need, want, and operation of the Bank.
• Collaborative team-player who can find creative and practical solutions in a dynamic work environment.
• Ability to handle ambiguity, juggle multiple matters at once, and quickly and seamlessly shift from one situation or task to another.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type 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.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking an Applied AI Analyst to support the design, configuration, testing, and monitoring of applied AI, Generative AI, machine learning, and agentic workflow solutions in a highly regulated banking environment. Working under the guidance of AI Scientists and in partnership with engineering, risk, and business teams, this role focuses on internal human-in-the-loop use cases such as AI-assisted loan documentation generation, fraudulent transaction detection models, policy and knowledge copilots, workflow automation, and other productivity solutions. A meaningful portion of the role is dedicated to AI solution intake and delivery support— learning new business domains, engaging business owners, preparing required documentation, and supporting vendor and risk reviews, so that solutions can be built and deployed under strict control gates and documentation standards aligned to internal and external regulations. The role emphasizes strong documentation, human oversight, privacy-by-design, cybersecurity, and disciplined lifecycle controls aligned to internal and external regulations. The role also emphasizes familiarity with Microsoft Foundry / Foundry Agent Service, approved Microsoft Copilot ecosystems, RAG architectures, and enterprise data platforms such as Snowflake.

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Applied AI solution development & analysis:

• Support AI Scientists in building, configuring, and testing applied AI/GenAI solutions for high-value banking use cases such as credit memo generation, policy/regulatory summarization, knowledge assistants, and internal productivity copilots.
• Develop and refine prompts, grounding instructions, structured outputs, evaluation datasets, and Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector search, document chunking, and metadata-driven retrieval.
• Prepare and transform structured and unstructured data; assist with API integrations, notebooks, and repeatable workflows that improve quality, traceability, and analyst productivity.

Agentic workflow design & orchestration:

• Assist in designing and testing agentic workflows using approved enterprise platforms and frameworks, including multi-agent patterns, human-in-the-loop approvals, handoffs, and subagent / agents-as-tools designs.
• Work with emerging interoperability patterns such as Model Context Protocol (MCP), tool / skill / plugin integration, and Agent-to-Agent (A2A) connectivity under supervision and within approved guardrails.
• Document workflow steps, tool schemas, fallback logic, escalation paths, and safe disablement / rollback procedures for agentic and GenAI solutions.

Microsoft Foundry, Copilot, and enterprise platform enablement:

• Support prototyping and evaluation in Microsoft Foundry / Foundry Agent Service and related Microsoft ecosystems (for example, Microsoft 365 Copilot) while partnering with Engineering and Data teams operating on Snowflake and other approved enterprise platforms.
• Assist with prompt and agent configuration, retrieval integration, logging, model / tool versioning, and operational runbooks.

Evaluation, testing, and monitoring:

• Create and execute test cases for accuracy, groundedness, hallucination, task completion, retrieval quality, bias/fairness, and basic adversarial or prompt-injection scenarios; escalate issues promptly.
• Track KPIs/KRIs, output quality, drift indicators, and user feedback; maintain evidence needed for pilot reviews, production monitoring, and periodic reassessment.

AI governance, intake documentation, and cybersecurity/privacy controls:

• Support AI use-case intake and governance processes by preparing required documentation (e.g., AI intake forms, model/system inventories, change-control artifacts, and audit-ready evidence packs) aligned to MCB’s Trustworthy & Responsible AI Principles and internal approval processes.
• Learn domain and process context for new use cases by speaking with business owners and control partners; translate requirements into clear problem statements, data needs, user journeys, control gates, and documentation required to comply with internal and external regulations.
• Support third-party / AI vendor due diligence by collecting and organizing evidence, reviewing vendor documentation, and helping risk-tier AI vendors and solutions in partnership with Third-Party Risk and Cyber/IT; act as an AI subject matter expert in providing an understanding of AI-specific risks.
• Apply privacy-by-design, data minimization, access-control, and secure prompt/data handling practices; follow approved tooling and build standards.

Cross-functional partnership and continuous learning:

• Communicate findings, limitations, and recommendations clearly to AI Scientists, managers, control partners (Model Risk, Compliance/Legal, Cyber/IT, Data Privacy), and business stakeholders; incorporate feedback quickly and accurately.
• Contribute to playbooks, standard operating procedures, and reusable templates for prompts, evaluations, agent patterns, and workflow controls.

Innovation and best practices:

• Stay current on practical applied-AI methods—including RAG, evaluation frameworks, agentic workflow design, MCP, A2A, and Microsoft Foundry capabilities—and recommend fit-for-purpose uses under established control gates.
• Demonstrate sound judgment, curiosity, and willingness to learn from senior AI Scientists while promoting responsible AI, reproducibility, and disciplined execution.

Qualifications & Skills:

• 2+ years of work experience.
• Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, Information Systems, Mathematics, or a related field is preferred. Relevant internships, apprenticeships, or comparable hands-on AI, analytics, or automation project experience will be considered.
• Working knowledge of Python, SQL, notebooks, REST APIs, JSON/YAML, and version control (e.g., Git) for data analysis and AI workflow support.
• Understanding of traditional machine learning model development and lifecycle concepts, including model training, data leakage prevention, testing/validation, monitoring, and common performance metrics for classification and regression.
• Familiarity with LLM application patterns, including prompt engineering, structured outputs, function/tool calling, Retrieval-Augmented Generation (RAG), embeddings, and vector search.
• Familiarity with Microsoft Foundry (including Foundry Agent Service), Microsoft 365 Copilot / Copilot Studio concepts, and approved enterprise data/AI platforms such as Snowflake.
• Understanding of agentic workflow concepts such as MCP servers/tools, skills/plugins, subagents or agents-as-tools, handoffs, human-in-the-loop controls, and A2A integration patterns.
• Ability to test and evaluate AI outputs for accuracy, groundedness, hallucination, retrieval quality, bias/fairness, and basic security misuse scenarios.
• Working knowledge of model and data governance concepts, including documentation, monitoring, change control, inventories, audit trails, and three-lines-of-defense oversight in a regulated environment.
• Strong written and verbal communication skills; ability to turn technical findings into clear summaries, test evidence, and action items for business and risk stakeholders.
• Analytical, organized, and adaptable mindset; ability to learn quickly, manage multiple workstreams, and balance innovation with risk discipline.

Preferred Qualifications & Skills

• Financial services exposure in fraud, AML/KYC/CDD/EDD, underwriting, commercial banking, treasury, policy governance, or contact center analytics.
• Hands-on experience with Microsoft Foundry / Foundry Agent Service, Azure AI Search or equivalent retrieval tooling, M365 Copilot / Copilot Studio, Snowflake, or similar enterprise AI platforms is a plus.
• Experience with RAG architectures, vector databases / vector search, document chunking, metadata extraction, OCR/document understanding, and prompt engineering.
• Exposure to agentic workflow patterns such as MCP tool integration, skills/plugins, handoffs, subagents, A2A, and evaluation frameworks for task completion and tool-call quality.
• Familiarity with LangChain, Semantic Kernel, LangGraph, Microsoft Agent Framework, or similar orchestration libraries/frameworks is a plus.
• Awareness of external regulations including SR 11-7, SR 23-4, AI use-case intake / inventory processes, privacy, cybersecurity, and third-party risk expectations in a regulated environment.
• Ability to work in a constantly evolving environment.
• Must have excellent written and verbal communication skills.
• Demonstrate analytical, troubleshooting, and problem-solving skills.
• The ability to learn new technologies quickly.
• Self-directed individual with strong organizational and communication skills.
• Ability to synthesize multiple sources of information with an understanding of the bigger picture needs and operations of the Bank.
• Collaborative team player who can find practical solutions in a dynamic work environment.
• Ability to handle ambiguity, manage multiple tasks at once, and shift effectively between priorities.

Potential Salary: $120,000 - $150,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type 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.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

MongoDB is a complex, mission-critical database server that operates in a wide range of environments. Customers rely on its ability to meet high standards for Performance, Security, Availability, and Correctness. Achieving these standards requires robust developer tooling for every layer of the stack, from the underlying C++ storage engine through our Atlas Cloud offering. The Developer Productivity organization plays a vital role in enabling MongoDB engineers to ship products that meet our high company standards.

The Build Team focuses on ensuring that our code is able to be packaged and shipped for all supported operating systems and architectures. We are responsible for ensuring that this build happens consistently, quickly, and correctly, and that we do as much as possible to ensure performance and correctness of the resulting binaries. Tooling changes can have a substantial impact on the final product we ship to customers, with tooling changes recently yielding a 10% improvement in the overall performance of the MongoDB database. Under the hood we use the Bazel build system in order to meet these goals and to handle the multi-language nature of code shipped at MongoDB. 

We are looking to speak to candidates who are based in New York City for our hybrid working model.

The ideal candidate should

• Have completed a relevant software development internship or similar summer research experience
• Have experience and interest in using and tuning AI tools to accelerate development velocity and improve code quality
• Be interested in learning about build systems such as Bazel and assembling and shipping highly complex software at scale
• Be interested in working specifically with C++, Rust, Python, and Java
• Demonstrate the ability to quickly learn, adapt to, and excel with new technologies, frameworks, and tools in dynamic environments

Expectations

• Update our tooling to improve the reliability, performance, and developer experience of the systems used every day by developers, locally and in our continuous integration environments
• Provide internal support for our systems, answering questions and addressing technical issues as they arise
• Learn about core software development principles around shipping code at scale, and grow your ability to contribute to the overall operational excellence of our build systems
• Demonstrate a strong empathy for our internal customers

Success

Three Months:

After three months, you will have made contributions to in-progress software development projects. You will be able to reliably work on small features and bugs. You will be expected to start looking for medium sized features and projects of approximately 2 weeks of effort.

Six Months:

You will have working knowledge of many of our build systems and be able to consistently deliver medium sized projects and features with low supervision in some areas, interfacing with customers and stakeholders. You will be suggesting appropriate smaller fixes and improvements to our codebase, and be able to provide input on smaller projects and features proposed by other members of the team.

One Year:

You will regularly be making contributions to technical projects that have a meaningful impact on our ability to reliably deliver a good experience for the developers that use our products at MongoDB. You will have strong knowledge of areas of our code that you have worked in, and will be able to provide some guidance on technical directions, with support from senior engineers.

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: 1273421176

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 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 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 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 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.

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 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 at the forefront of the AI revolution, helping the U.S. government unlock the potential of AI across national security missions. We’re building enterprise-grade generative AI solutions and delivering them into operational use cases that matter.

The Global Forward Deployments (GFD) organization operates as a critical horizontal layer across Scale, sitting at the intersection of Engineering, Product, Design (EPD), Delivery, and GTM. As our business scales, we are growing the GFD Project Management Office (PMO) to act as the connective tissue that brings structure to ambiguity by aligning teams, organizing cross-functional workstreams, and keeping priorities coordinated across the organization.

As a Technical Program Manager within this expanding PMO, you will drive execution across diverse initiatives by partnering closely with Infrastructure & Security, Product, Software Engineering, Machine Learning, Mission/Field Engineering, Delivery, and Go-To-Market (GTM) teams. Your focus will be integrating engineering roadmaps, customer delivery timelines, and security constraints to enable successful deployments in complex, isolated environments.

What You Will Do

• Lead as a Horizontal PMO Partner: Serve as a central node within the growing GFD PMO, driving alignment across Engineering, Product, and Design (EPD) initiatives and ensuring priorities remain top-of-mind across the organization.
• Spearhead Niche Initiatives: Take on Scale’s difficult-but-ambiguous problems, breaking them down in a structured way and driving them to successful outcomes. You will dive into both technology and organizational processes to craft effective solutions and gain efficiencies, track resourcing and vendor management, and align internal resources to solve unique organizational, and technical challenges. 
• Bridge EPD, Delivery, and GTM: Act as the primary technical program manager uniting GFD with Product, ML, Mission & Field Engineering, Delivery, and GTM teams to wrangle contractual deliverables across EPD, unblock complex custom integrations, and drive technical milestones against critical contract checkpoints.
• Optimize Cross-Functional Processes: Collaborate with stakeholders across the company to improve processes and procedures, ensuring Scale's continued success.
• Foster Communication: Create an effective feedback loop between all teams within EPD as well as with partner teams like Legal, BizOps, and Partnerships.
• Navigate Ambiguity: Transition AI/ML technologies and processes into working Public Sector products/solutions even when requirements are undefined or ambiguous.

Ideally You’d Have

• Current or past Security Clearance (TS/SCI preferred).
• Proven experience partnering closely with Product and cross-functional Engineering teams to align technical roadmaps, manage dependencies, and drive complex, multi-team initiatives.
• Experience in project management, including planning, organizing, and managing resources.
• A demonstrated capacity to operate effectively and maintain high-quality output within a high-tempo, ambiguous, or chaotic environment.
• Experience in security and compliance, with a focus on cross-departmental collaboration.
• Experience in delivering secure and reliable solutions within classified, isolated, and air-gapped environments.
• Demonstrated understanding of security practices within cloud environments (e.g., AWS, Azure, GCP).
• Experience in a high growth, fast-paced technology company.
• An action-oriented mindset, balancing creative problem-solving with a strong drive to achieve outcomes.

Nice to Haves

• Experience in microservice design and Kubernetes-based container orchestration.
• Experience applying AI or Machine Learning.
• Strong analytical skills, with experience using data analysis tools or software.
• Demonstrated history of fostering cross-functional collaboration with Delivery, Sales, and Engineering teams.
• Backlog refinement & roadmapping experience with tools like Linear and JIRA.
• Proven experience translating complex SOW requirements into tactical engineering deliverables 
• Experience maintaining alignment with organizational capacity planning and delivery timelines.
• Background in Software, Security, or System Engineering.

(Note this role must be based within the continental United States and requires current US Citizenship to support Scale’s Public Sector business.)

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)

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.

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.

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 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

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.

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

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

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

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

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

Ideally you will have: 

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

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As a Senior Value Engineering Consultant specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As an Senior Value Engineer specializing in CPG and Fleet Logistics, you are pushing the envelope in solving business-critical problems for some of the world's most recognized consumer brands and global mobility networks. You will be working intimately with our most strategic enterprise clients, understanding their uniquely complex objectives—spanning from high-velocity beverage manufacturing and Direct Store Delivery (DSD) optimization to massive-scale fleet lifecycle management and dynamic asset routing. You will build Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers' massive supply chains, vehicle fleets, and distribution networks. This enables them to industrialize AI, unlocking real ROI on deployments at scale—ensuring products are always on the shelf and vehicles are always ready for the customer. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Chief Supply Chain Officers (CSCOs) and Fleet Operations Executives, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis across these premier global networks.

Key Responsibilities:

• AI Discovery & Solutioning: Understand the clients' overarching AI strategies and the distinct supply chain challenges inherent to high-volume CPG and fleet mobility (e.g., predictive demand forecasting, route optimization, fleet predictive maintenance, dynamic asset allocation, and mitigating raw material volatility). As a Celonis product and logistics domain expert, translate these complex, physical-world challenges into innovative AI solutions that drive measurable impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle within various manufacturing, distribution, and fleet management business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and telematics networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, and DSD execution.

• Agentic Process Transformation: Support these enterprise clients in achieving tangible ROI from AI at scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous fleet rebalancing, intelligent shipment exception handling, or automated trade promotion deductions).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs (e.g., SAP), Transportation Management Systems (TMS), Warehouse Management Systems (WMS), and massive IoT/telematics data streams.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for CPG and Mobility Supply Chains, scaling knowledge across the organization regarding the nuances of fast-moving consumer goods and asset-heavy fleet operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, CPG/Beverage, or Fleet Logistics environments. This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume manufacturing and mobility (such as Direct Store Delivery (DSD), Order-to-Cash, Procure-to-Pay, Fleet Lifecycle Management, or Sales & Operations Planning) with the ability to translate high-level operational needs into specific AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent dispatch assistants, or automated extraction of data from complex vendor contracts and logistics documentation).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional and IoT datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, logistics directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for enterprise-grade supply chain environments.

• Familiarity with CPG and fleet-specific systems (e.g., SAP APO/IBP, Blue Yonder, Manhattan, or major telematics/fleet tracking platforms).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

About the Role

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

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

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

What This Team Owns

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

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

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

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

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

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

What You’ll Do

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

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

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

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

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

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

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

You May Be a Good Fit If You Have

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

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

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

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

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

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

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

Strong Candidates May Also Have

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

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

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

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

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

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

Role Description

• As an Applied AI Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 7+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

You will join the global Security function, which is responsible for safeguarding QRT’s technology platforms, data, and operational environments. The team partners closely with Engineering, Infrastructure, Risk, Compliance, and business stakeholders to design and implement security controls, reduce risk, and enable safe, high-performance operations across global offices.

Your future role within QRT

• Support the implementation of security controls and processes for product security, focusing on a broad range of systems, including core trading infrastructure, cloud services, and business applications across both Windows and Linux environments.
• Collaborate with engineering and product teams to integrate security into product design and development, applying your experience in securing large-scale software systems in a fast-moving environment.
• Contribute to the development and maintenance of a secure software development lifecycle (SDLC) with a focus on secure coding practices in languages like Python, C++, Rust, Go and Kotlin/Java.
• Conduct threat modeling, vulnerability assessments and security code reviews across different platforms, ensuring security is embedded at every stage of the development lifecycle.
• Provide mentorship, guidance, and training on security best practices and secure development processes to engineering teams working in mixed cloud and operating systems environments.
• Perform vendor security reviews to assess third-party security practices and ensure compliance with QRT’s standards.
• Integration of security scanning tools (SAST, DAST, etc.) into CI/CD pipelines and runtime environments to ensure continuous security monitoring and threat detection across Alibaba Cloud, AWS, Azure, and on-prem systems.
• Proactively identify security risks and develop strategies for risk mitigation in a fast-paced high-stakes environment.

Your present skillset

• At least 7 years of experience in product security or similar roles with significant practical experience in securing software development at scale.
• Proven record of accomplishment in secure coding practices and development experience in development languages such as Python, C++, Rust, Go and Kotlin/Java.
• Strong technical background in software development, system architecture and security tools.
• Strong understanding of security principles, techniques and technologies related to software and product security, cloud platforms and business applications. Knowledge of low-latency financial systems would be an advantage.
• Experience working with and securing both Windows and Linux-based systems.
• Extensive experience with one or more cloud platforms such as AWS, Microsoft Azure and Alibaba Cloud used in a hybrid environment.
• In-depth knowledge of threat modeling, risk assessment and development of mitigation strategies for large-scale, complex systems in a fast-paced environment.
• Experience integrating security scanning tools into CI/CD pipelines and runtime environments.
• Experience conducting vendor security reviews and managing third-party security assessments.
• Excellent leadership, problem-solving, communication and adaptability skills, suited for a senior-level position in a fast-paced environment.

Base salary range for this position is $160,000 to $220,000 per year. 

QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

The Strategic Account Director position is responsible for developing and managing Accounts designated as Global Accounts and maximizing all sales opportunities within those accounts. More specifically, this position will be charged with promoting and selling KnowBe4’s products and services, with the objective to achieve and exceed monthly sales quota. This can be achieved by targeting your book of business and maximizing cross sale opportunities, increasing subscription levels and adding on additional seats due to account growth. This role will work closely with the assigned customer account teams including the Customer Success Manager and other Account Executives/Managers as necessary to ensure increased ARR and more product suite adoption and coordinate any territory specific deals relating to their global accounts.

Responsibilities:

• Promote and sell KnowBe4’s range of products and services.
• Build and maintain a pipeline of potential customers by developing and managing relationships with prospects.
• Build and maintain a pipeline of potential cross sale, add-on and upgrade opportunities by developing and managing relationships with your assigned customer accounts.
• Identify key decision makers and develop meaningful relationships that add value and drive future account growth. 
• Articulate the value proposition of KnowBe4’s full suite of products and help the customer understand how it will improve their business’s security awareness training (and security overall).
• Achieve or exceed monthly quotas and/or targets. 
• Be well versed in KnowBe4’s product offerings and promote the products and services at trade shows as requested.
• Follow up on marketing leads to generate sales opportunities and pipeline.
• Act strategically in offering or negotiating discounted pricing, in line with established policies and procedures.
• Maintain accurate and thorough records for customer calls, emails, notes, tasks, demos and other relevant information in compliance with the Administration Policy.
• Support in the renewal process where there is an opportunity to grow the account.
• Work with those Customer Success Managers and Renewal Specialists assigned to your customer accounts to the end of your customers increasing their commitment and use of the KnowBe4 Product Suite. 
• Partner with KnowBe4 Revenue teams on methods/ strategies to achieve increased account penetration of Global accounts.  
• Global Account Mapping.
• Traveling to meet on-site with C-Levels and other Executives for their assigned accounts.

Minimum Qualifications:

• Bachelor's Degree strongly preferred (exceptions may be made for military experience). Degree in any field acceptable, but a plus if Cybersecurity, Computer Science, IT, Business, Marketing. 
• Proven track record selling to EVP and C-level (CISOs and Security Teams a plus)
• 5+ years SaaS sales experience (Cybersecurity preferred but not required)
• Experience selling deals $100K - $200K in the Enterprise segment
• Experience selling multi-year deals
• International: English and local language proficiency required.
• Has demonstrated expertise in value-based selling methodologies with enterprise accounts
• Executive-level presentation and communication skills 
• Experience with strategic account planning and management showing measurable account growth
• Experience managing and progressing opportunities involving multiple stakeholders
• Has a track record of managing and closing complex, multi-year deals with multiple stakeholders
• Experience creating and communicating compelling business cases 
• Experience with consultative selling approach and value selling methodology
• Experience handling technical objections
• Skilled in running discovery conversations and managing tailored product demonstrations 
• Technical aptitude with experience using sales tools 
• Experience with CRM systems (preferably Salesforce)
• Experienced with pipeline management & accurate forecasting
• Familiarity with standard concepts, practices and procedures within the IT Security Field
• Experience with Salesforce and Gmail
• Network or Security Plus preferred
• Achievement in demanding extracurricular activities (e.g., debate team captain, entrepreneurial ventures)
• Self-motivated with a growth mindset and continuous learning orientation 
• Strong competitive spirit balanced with collaborative approach 
• Demonstrated interest in cybersecurity sales
• Consistently positive attitude even in the face of adversity
• Quick learner with strong listening skills
• Strong written and verbal communication skills, with previous presentation experience
• Excellent phone presence and professional demeanor 
• Time management and organizational skills 
• Ability to handle rejection and maintain persistence
• Stats driven business professional
• Motivated, energetic self-starter
• Strong collaborative and teamwork skills
• Must be able to work with minimum supervision
• General understanding of:
• Human Risk Management & challenges faced by IT / InfoSec Teams / Compliance & Board Members
• Basic network and email security concepts
• SIEM/SOAR platforms
• Zero Trust Architecture
• Cloud security architecture
• Phishing attack vectors 
• Identity & Access Management 
• Security orchestration and automation
• General understanding of Security Technology Stack: 
• Enterprise IAM solutions (Okta, Ping, Azure AD) 
• SIEM platforms (Splunk, QRadar, LogRhythm) 
• EDR platforms (CrowdStrike, Carbon Black, SentinelOne) 
• Cloud security (AWS Security Hub, Azure Security Center) 
• Email security solutions 
• GRC platforms
• Genuine curiosity and strong desire to learn about cybersecurity and technical concepts
• Basic computer literacy and comfort with business applications
• Ability to quickly grasp and explain basic technical concepts
• Ability to translate complex topics into simple terms
• Interest in keeping up with current technology and cybersecurity trends
• Proven track record of grit and resilience in challenging situations, with high performance under pressure 
• Collegiate athlete or competitive sports background demonstrating rigorous discipline, teamwork, dedication, and competitive spirit
• History of setting and achieving ambitious personal or professional goals
• Track record of leadership in team settings

The compensation for this position ranges from $250,000-$270,000 including base, bonuses and commissions. For more details, click here www.know www.knowbe4.com/careers/know-your-pay/enterprise-sales

New York positions open to candidates located in the New York area.

The Account Manager (Enterprise/Strategic) position is responsible for managing assigned customer accounts and maximizing all sales opportunities within those accounts. More specifically, this position will be charged with promoting and selling KnowBe4’s additional products and services to businesses (organizations with 1501+ employees), with the objective to achieve and exceed monthly sales quota. This can be achieved by targeting your book of business and maximizing cross sale opportunities, increasing subscription levels and adding on additional seats due to account growth. This role will work closely with the Customer Success Manager to ensure increased ARR and more product suite adoption by our customers.

Responsibilities:

• Promote and sell KnowBe4’s range of products and services
• Build and maintain a pipeline of potential cross sale, add-on and upgrade opportunities by developing and managing relationships with your assigned accounts
• Identify key decision makers while developing and qualifying cross sale, add-on and upgrade opportunities
• Articulate the value proposition of KnowBe4’s full suite of products and help the customer understand how it will improve their business’s security awareness training (and security overall)
• Achieve or exceed monthly quotas and/or targets 
• Be well versed in KnowBe4’s product offerings and promote the products and services at trade shows as requested
• Follow up on marketing leads to generate sales opportunities and pipeline
• Act strategically in offering or negotiating discounted pricing, in line with established policies and procedures
• Maintain accurate and thorough records for customer calls, emails, notes, tasks, demos and other relevant information in compliance with the Administration Policy
• Support in the renewal process where there is an opportunity to grow the account
• Work with those Customer Success Managers and Renewal Specialists assigned to your customer accounts to the end of your customers increasing their commitment and use of the Knowbe4 Product Suite

Minimum Qualifications:

• Bachelor's Degree strongly preferred (exceptions may be made for military experience). Degree in any field acceptable, but a plus if Cybersecurity, Computer Science, IT, Business, Marketing.
• Proven track record selling to EVP and C-level (CISOs and Security Teams a plus)
• 5+ years SaaS sales experience (Cybersecurity preferred but not required)
• Experience selling deals $500K+ in the Enterprise segment
• Experience selling multi-year deals
• International: English and local language proficiency required.
• Has demonstrated expertise in value-based selling methodologies with enterprise accounts
• Executive-level presentation and communication skills 
• Experience with strategic account planning and management showing measurable account growth
• Experience managing and progressing opportunities involving multiple stakeholders
• Has a track record of managing and closing complex, multi-year deals with multiple stakeholders
• Experience creating and communicating compelling business cases 
• Experience with consultative selling approach and value selling methodology
• Experience handling technical objections
• Skilled in running discovery conversations and managing tailored product demonstrations 
• Technical aptitude with experience using sales tools 
• Experience with CRM systems (preferably Salesforce)
• Experienced with pipeline management & accurate forecasting
• Familiarity with standard concepts, practices and procedures within the IT Security Field
• Experience with Salesforce and Gmail
• Network or Security Plus preferred
• Proven track record of grit and resilience in challenging situations, with high performance under pressure 
• Collegiate athlete or competitive sports background demonstrating rigorous discipline, teamwork, dedication, and competitive spirit
• History of setting and achieving ambitious personal or professional goals
• Track record of leadership in team settings
• Demonstrated interest in cybersecurity sales
• Quick learner with strong listening skills
• Strong written and verbal communication skills, with previous presentation experience
• Excellent phone presence and professional demeanor 
• Time management and organizational skills 
• Ability to handle rejection and maintain persistence
• Stats driven business professional
• Motivated, energetic self-starter
• Strong collaborative and teamwork skills
• Must be able to work with minimum supervision
• Must have a General understanding of:
  • Human Risk Management & challenges faced by IT / InfoSec Teams / Compliance & Board Members
  • Basic network and email security concepts
  • SIEM/SOAR platforms
  • Zero Trust Architecture
  • Cloud security architecture
  • Phishing attack vectors 
  • Identity & Access Management 
  • Security orchestration and automation
• General understanding of Security Technology Stack:
  • Enterprise IAM solutions (Okta, Ping, Azure AD) 
  • SIEM platforms (Splunk, QRadar, LogRhythm) 
  • EDR platforms (CrowdStrike, Carbon Black, SentinelOne) 
  • Cloud security (AWS Security Hub, Azure Security Center) 
  • Email security solutions 
  • GRC platforms
• Genuine curiosity and strong desire to learn about cybersecurity and technical concepts
• Basic computer literacy and comfort with business applications
• Ability to quickly grasp and explain basic technical concepts
• Ability to translate complex topics into simple terms
• Interest in keeping up with current technology and cybersecurity trends
• Proven track record of grit and resilience in challenging situations, with high performance under pressure 
• Collegiate athlete or competitive sports background demonstrating rigorous discipline, teamwork, dedication, and competitive spirit
• History of setting and achieving ambitious personal or professional goals
• Track record of leadership in team settings

The compensation for this position ranges from $200,000-$210,000 including base, bonuses and commissions. For more details, click here www.know www.knowbe4.com/careers/know-your-pay/enterprise-sales

We will accept applications until 2/27/2026.

MongoDB is seeking a Director, Global Process Owner (GPO) – Quote-to-Cash to serve as the single-threaded owner of the company’s end-to-end Quote-to-Cash process architecture across Cloud, Enterprise Advanced (EA), and Professional Services.

This role is responsible for designing and governing scalable, durable Quote-to-Cash processes that support MongoDB’s evolving business models, product offerings, and global growth. The Director, GPO – Quote-to-Cash establishes global process standards, resolves design tradeoffs across functional pillars, and ensures Finance processes scale efficiently as transaction complexity and volume increase.

This leader acts as Finance’s primary process design partner to IT, Product, Engineering, Deal Strategy, and Go-to-Market teams, ensuring that new products, monetization models, and operational workflows are implemented in a controlled and scalable manner.

Importantly, this role does not run the close or manage transactional accounting or operational processing teams. Instead, the role focuses on long-term process architecture, operating model design, and structural simplification across the Quote-to-Cash ecosystem.

The ideal candidate combines deep understanding of Quote-to-Cash processes with strong systems thinking, operational design capability, and cross-functional influence in a high-growth public-company environment.

We're looking to speak with candidates based in New York City or Austin for our hybrid working model.

Key Responsibilities

End-to-End Quote-to-Cash Process Ownership

• Serve as the single global owner of MongoDB’s Quote-to-Cash process architecture across:
• Cloud / consumption-based offerings
• Enterprise Advanced (EA)
• Professional Services
• Define and maintain globally consistent process standards, governance models, and design principles across the Quote-to-Cash lifecycle
• Ensure process decisions are scalable across evolving products, pricing models, geographies, and routes to market

Process Architecture & Operating Model Design

• Design scalable end-to-end workflows spanning:
• Deal structure and approvals
• Order flows
• Billing and invoicing
• Revenue-impacting operational workflows
• Customer lifecycle transitions and renewals
• Identify structural inefficiencies, fragmented ownership models, and manual dependencies across the Quote-to-Cash ecosystem
• Drive simplification and standardization efforts that reduce operational complexity and improve scalability

Cross-Functional Governance & Tradeoff Resolution

• Act as Finance’s primary design partner to:
• IT and Finance Systems
• Product and Engineering
• Deal Strategy and Go-to-Market Operations
• Revenue Accounting and Order-to-Cash
• Resolve cross-functional tradeoffs between process scalability, customer experience, operational efficiency, and control requirements
• Establish governance mechanisms for prioritizing and evaluating Quote-to-Cash process changes

New Products & Monetization Models

• Lead the operational process design for new products, pricing constructs, and monetization models
• Ensure new revenue motions are operationally supportable before launch and can scale without disproportionate manual intervention
• Partner with Technical Revenue Accounting and operational teams to ensure process flows support accounting, billing, and reporting requirements

Transformation & Continuous Improvement

• Build and maintain a multi-year Quote-to-Cash transformation roadmap aligned with company growth objectives
• Drive initiatives focused on:
• Reducing manual intervention
• Improving workflow automation
• Clarifying ownership boundaries
• Increasing operational scalability
• Establish process metrics and governance frameworks to measure process health and organizational efficiency

Success Metrics

Success in this role is measured by

• Sustained reduction in manual intervention and workflow exceptions
• Fewer cross-functional escalations tied to process ambiguity or design gaps
• Improved scalability of Quote-to-Cash operations as the business grows
• Stable Finance operational headcount relative to revenue growth
• Successful operationalization of new business models without downstream disruption

Qualifications

Required

• 10+ years of experience in Quote-to-Cash, Revenue Operations, Revenue Accounting Operations, Finance Transformation, or related functions
• Deep understanding of end-to-end Quote-to-Cash workflows in a SaaS or consumption-based business model
• Proven experience designing and scaling global operational processes in a high-growth public-company environment
• Strong cross-functional leadership skills with experience influencing Product, Engineering, IT, Finance, and GTM organizations
• Demonstrated ability to resolve complex operational tradeoffs and drive organizational alignment

Preferred

• Experience supporting cloud or usage-based monetization models
• Experience leading enterprise-scale process transformation initiatives
• Familiarity with revenue accounting and billing operational requirements under ASC 606
• Experience operating in complex multi-system environments

Leadership Attributes

• Systems Thinker: Designs processes that scale across products, geographies, and operating models
• Architect, Not Operator: Focuses on structural design and long-term scalability rather than day-to-day transaction execution
• Cross-Functional Influencer: Aligns diverse stakeholders without relying on formal authority
• Simplifier: Reduces complexity, ambiguity, and manual effort across workflows
• Outcome-Oriented: Measures success through scalable operational outcomes, not activity volume

Why This Role Matters

As MongoDB continues to evolve its products, pricing models, and global operations, scalable Quote-to-Cash process architecture becomes increasingly critical. This role ensures that Finance can support business growth without linear operational complexity, enabling durable scale across systems, teams, and workflows.

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: 1273373045

The Position

Our DevOps Engineer must have a strong technical background in Azure, development, and operations processes, as our firm implements an aggressive and exciting cloud strategy. This role will facilitate and develop streamlined processes and work collaboratively with cross-functional teams of software engineers, data engineers, product and project managers, business analysts, and infrastructure architects. This individual must thrive in a fast-paced environment and be self-motivated with a passion for problem-solving and innovation. Our IT department is project-focused, undergoing a complete digital business transformation for the firm. This position will drive new possibilities and opportunities for teams to learn cutting edge technologies while ensuring current systems are supported at their best.

Key Responsibilities

• Create and maintain highly scalable Azure infrastructure using Microsoft Bicep and PowerShell
• Create and maintain Azure DevOps YAML CI/CD pipelines and environments
• Assist with Azure infrastructure or application code related troubleshooting
• Maintain proper user access to infrastructure and applications with EntraID and Azure IAM
• Perform periodic application security and code quality reviews with Snyk and Sonar Cloud
• Create modern automated cloud first solutions
• Attend daily Agile Standup and report on work progress
• Assist IT teams with onboarding new Azure infrastructure
• Recommend best DevOps practices based on industry standards

Qualifications

• 3+ years of experience deploying and maintaining Azure PaaS resources
• 3+ years of experience with Azure DevOps Repos and Pipelines
• 3+ years of experience with languages such as PowerShell, C# and Python
• 2+ years of experience with Infrastructure as Code (AzureRM, Bicep, Terraform, etc)
• Experience with EntraID or AD, and Identity and Access Management (IAM)
• Familiarity with containerization (Docker, Azure Container Apps, AKS, etc)
• Familiarity with Atlassian product suite, i.e. Jira, Jira SM, and Confluence
• Ability to clearly articulate DevOps best practices and concepts to Development and IT Teams
• Ability to translate technical requirements into work product that meet business needs
• Microsoft Certification a big plus (AZ-104, AZ-204, AZ-305, AZ-400, AZ-500, AZ-900)
• Experience with shift left code security practices (Snyk, etc.) a big plus
• Experience with code quality tools (Sonar, etc.) a big plus
• Experience developing software a plus

Education

• Bachelor of science degree (or equivalent) in Computer Science, Engineering, or relevant field
• Experience in developing/engineering applications for a large company

MongoDB is seeking a highly motivated Director of Strategic Sourcing to lead a globally distributed team of Procurement professionals.  This role is responsible for driving complex strategic sourcing strategies across all spend categories in support of the company’s business strategies.  As a key member of the Source-to-Pay cross functional team, you will be called upon to fly at different altitudes to help executives and individual contributors make better purchasing decisions.

The ideal candidate is a self-starter who has the knowledge, skill, and discipline to transform the function into our next stage of growth.  You should have deep expertise in driving technology deals such as public cloud infrastructure agreements, SaaS, IT services, while still having working knowledge of Marketing, professional services, and other indirect categories.

This will be a hybrid in-office role. We are looking for candidates who plan to be available in our New York City office for approximately 2 days per week.

Key Responsibilities: What You’ll Be Doing 

• Drive category strategy to all applicable spend categories for MongoDB
• Develop and maintain global procurement policies and procedures
• Develop, coach, and lead a high-performing global procurement team, while fostering a culture of continuous improvement, accountability, knowledge sharing, and innovation
• Be the face of Procurement by developing and maintaining strong relationships with key leaders and stakeholders and reinforcing the strategic value that the team provides
• Deliver annual cost savings target and multi-year pipeline based on assigned projects
• Implement and lead process improvement projects along with any change management required

Qualifications: What We’ll Need to See 

• Bachelor’s degree in Engineering, Supply Chain, Finance, or similar quantitative related field
• Procurement professional certification, such as CPSM, CIPS, CSP
• 12+ overall years of professional business experience
• 10+ years of progressive experience in Procurement and/or Strategic Sourcing
• 3+ years of people leadership experience
• Deep knowledge of strategic sourcing and negotiation
• Hands-on experience in negotiating complex deals
• Leader with vision and credentials working at global large scale companies
• Strong interpersonal and leadership skills
• Ability to drive change and influence all levels of the organization
• Experience analyzing large data sets while developing and driving recommendations from collected insights

How To Stand Out From Other Candidates 

• MBA or equivalent experience
• Working knowledge of Source to Pay Orchestration tools
• Experience with large ERP systems such as NetSuite, Oracle, SAP, or Workday
• Experience using Coupa (including Coupa Analytics and SIM)
• Experience working in multiple industries especially in the high tech sector
• Experience sourcing cloud infrastructure, SaaS, professional services, marketing
• Excellent presentation skills (both oral and written)
• High attention to detail
• Ability to operate as a Strategic Partner in a dynamic and ambiguous environment (e.g. able to quickly adapt to changing priorities)

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: 1273415385