Lifecycle Senior Specialist Contract Management Jobs

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Lifecycle Growth Marketing team engages with millions of Lyft riders and drivers to drive preference and usage of Lyft. The team runs hundreds of acquisition, engagement, retention and resurrection experiments every year across email, push notifications, SMS and in-app messaging surfaces. We are data-driven in everything we do. We test and measure all of our communications and tailor experiences to be personalized and contextual by audience segment. In this role, you will work closely with Product, Engineering, Analytics, Data Science, and Marketing Operations to design, test and optimize incentive and non-incentive messages and experiences. Responsibilities: Own the lifecycle marketing strategy for your audience — define the channel mix, set the prioritization framework, and ensure every communication delivers clear value to the target user Build and manage an experimentation program that drives measurable impact — from ideation through results, with a clear point of view on what to test Partner with Engineering, Product, and Data Science to unlock new platform capabilities, influence roadmaps, and push beyond out-of-the-box tooling Own performance reporting — define metrics, experimentation setup, and share results and next steps with stakeholders and leadership Drive creative strategy — brief, review, and iterate on assets across email, push, SMS and in-app with a strong feedback loop with designers and copywriters Apply behavioral science frameworks to inform message sequencing, timing, and incentive design Experience: 6+ years in growth marketing. You've owned a full lifecycle marketing program from the ground up — not just executing campaigns, but building strategy from high-level goals and managing a prioritized roadmap Strong SQL skills required — you’re comfortabl

This role oversees the lifecycle of forward-deployed engineering engagements in which MongoDB Forward Deployed Engineers (FDEs) partner closely with customer engineering teams to build working agents. It is a high-impact role at the intersection of customer delivery, AI agent development, and product feedback. By working closely with customers during implementation, the Sr. Technical Program Manager helps shape real-world agent outcomes, demonstrate the value of MongoDB’s platform in live enterprise environments, and bring back insights that can inform future product direction. These engagements are designed to help customers realize business value from our platform, accelerate successful agent delivery, and generate product feedback through close collaboration during implementation. The Sr. Technical Program Manager, FDE Engagements drives successful delivery by aligning stakeholders, managing risks and dependencies, removing operational blockers, and ensuring clear ownership, communication, and decision-making across the engagement lifecycle. In partnership with FDE, Product, Engineering, account teams, and customer stakeholders, this role is accountable for program execution and engagement outcomes. If an action item does not yet have an explicitly assigned owner, the Sr. Technical Program Manager is responsible for driving assignment and follow-through until ownership is clear. Pre-customer environment access Main goals: Secure access to the customer's internal collaboration and development tooling as early as possible Align on the intended behavior, functionality, and architecture of the agents Define how the FDE team and customer engineering team will collaborate on use case and architecture definition, code, and execution Establish the deployment path for MongoDB’s tools across customer development and cloud environments Confirm business goals, technical scope, and success criteria for the engagement During this phase, the Sr. Technical Program Manager partne

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. This is a dedicated identity engineering role on our Enterprise Cloud Engineering team. You will own and operate the enterprise identity and access platforms — Okta, Microsoft Entra ID, and modern IGA systems — that govern how every employee, application, service, and AI agent authenticates and is granted access at scale. Our team builds the authentication, authorization, identity governance, and identity lifecycle capabilities that keep Snowflake secure and compliant, partnering closely with Security and Engineering to deliver secure-by-default, Zero Trust access. These identity p

A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What you'll do Lead the design, development, and operation of scalable, enterprise-grade AI/ML architectures and systems with a strong emphasis on reliability, availability, and performance. Lead and mentor a team of engineers, driving technical direction, code quality, and iterative delivery of large-scale solutions. Partner closely with data scientists, engineers, product teams, and compliance to integrate AI/ML solutions into existing and new products. Own the end-to-end lifecycle of GenAI services, including LLM inference, model serving, and proxy/gateway layers that support multiple downstream applications. Define and uphold engineering best practices around observability, scalability, security, and cost efficiency for AI/ML platforms. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies, and translate them into pragmatic solutions for the business. Ensure compliance with industry standards and best practices in AI/ML. What's required Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in software/AI/ML engineering, with a proven track record of successful delivery of complex, production-grade systems. Demonstrated experience building large-scale enterprise-grade services with high reliability, availability, and observability (SLO/SLA-driven en

Project Manager will oversee the entire project lifecycle, ensuring quality standards and project requirements are met. Responsibilities include developing project plans, managing resources and budgets, and collaborating with cross-functional teams to achieve project objectives. Source: Adani Group | Job ID: 46379

Project Contracts Manager is responsible for overseeing the entire project lifecycle, from initiation to closure, with a focus on effective contract management. This role involves leading project contracts, managing contract negotiations and executions, ensuring project goals are met, and maintaining high standards of quality and compliance. Source: Adani Group | Job ID: 54186

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. Within Safety Systems, the Model Policy team works to ensure that frontier models behave safely and reliably in real-world environments by designing policies that define safe model behavior. Some of our publications include: Safety at every step OpenAI GPT6 System Card OpenAI Model Spec About the Role We’re hiring a Model Policy Manager to shape model behavior for U.S. government use, with a focus on national security applications. You’ll define nuanced policies and translate them into training and evaluation criteria, helping models navigate high-stakes scenarios while preserving their usefulness and capabilities. In this role, you will: Develop model policies that guide safe and useful behavior. Build evaluations, identify policy gaps and model failures, and use findings to improve policies and training. Work with research, engineering, and domain experts to support safe, reliable deployment. You might thrive in this role if you: Bring relevant experience in AI safety, policy, or risk assessment. Have strong judgment and can turn complex safety questions into clear, practical policies. Have the technical fluency to work hands-on with model data and evaluations. Are motivated by OpenAI’s mission and the responsible use of

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. Within Safety Systems, the Model Policy team works to ensure that frontier models behave safely and reliably in real-world environments by designing policies that define safe model behavior. Our relevant publications include: Safety at every step OpenAI GPT6 System Card OpenAI Model Spec GPT-Live ChatGPT Images 2.5 About the Role We are hiring a Model Policy Manager to focus on the safety of multimodal models. In this role, you will shape how OpenAI identifies, evaluates, and addresses risks in multimodal AI models - such as GPT-Live and ChatGPT Images - as well as multimodal capabilities in frontier AI models. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and maintain model policies for audio, image, video, and omni-modal behavior. Translate theories of harm and threat models into behavioral safety policies, evaluation criteria, grading guidance, and safeguards. Identify and analyze safety regressions and failure patterns to identify gaps in existing policies and inform policy iteration. Develop policy artifacts that support model training, evaluation, and deployment, including behavior i

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse, misalignment, and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. About the Role We are hiring a Product Manager to focus on risk related to multimodal models. In this role, you will drive initiatives which ensure that OpenAI’s audio, image, and video deployments are safe, impactful, and aligned with user needs and technical innovation. You will clarify strategic priorities, develop safety-focused product roadmaps, and collaborate closely with AI researchers, software engineers, policy experts, and cross-functional partners. This role suits a proactive, technically skilled product manager adept at adversarial thinking and excited to tackle challenging, ambiguous problems through structured analysis and collaborative decision-making. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Partner closely with AI research, engineering, data science, policy teams, and other stakeholders to embed safety throughout the development and deployment of multimodal AI models - such as GPT-Live and ChatGPT Images - as well as multimodal capabilities in frontier AI models. Develop comprehensive frameworks for understanding and mitigating deployment safety risks, drawing on data analysis, expert consultation, and adversarial assessments. Define strate

The Cyber Deployment Manager partners with customers throughout the full lifecycle—from technical discovery and solution design through implementation, deployment, and adoption. You’ll work closely with Sales and Solutions Engineering during the pre-sales process to understand customer security priorities, assess technical requirements, develop solution architectures, and support demonstrations, workshops, and proofs of concept. After a customer commits, you’ll remain engaged as the technical deployment lead, translating the proposed solution into a production-ready implementation. You’ll guide integrations, establish success criteria, manage technical risks, and help customers operationalize AI across security workflows such as secure code review, vulnerability management, threat detection, incident response, SOC operations, and GRC automation. In this role, you will: Lead technical discovery with security executives, practitioners, architects, and engineering teams. Partner with Sales and Solutions Engineering on solution design, demonstrations, workshops, technical validation, and proofs of concept. Translate customer requirements into clear architectures, deployment plans, success criteria, and implementation milestones. Own the transition from pre-sales solution design into post-sales deployment and adoption. Serve as the primary technical partner during implementation, coordinating customer stakeholders and internal Product, Engineering, Security, and GTM teams. Build and troubleshoot integrations involving APIs, agents, security tools, cloud platforms, data sources, and enterprise workflows. Identify deployment risks, technical blockers, and product gaps, and drive them toward resolution. Help customers establish evaluation frameworks, governance controls, guardrails, monitoring, and human-review processes. Measure adoption and business impact, ensuring deployed solutions deliver meaningful security outcomes. Turn successful customer deployments into reusable

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. About the Role The Safety Measurement Product Manager owns OpenAI's approach to measuring harm and safeguard efficacy in production, including driving the strategy for our suite of safety measurement platforms and products used across the company. You will partner closely with our safety research and engineering teams to determine what we measure, where we measure it, and how we measure it, feeding those insights directly into critical leadership decisions and back into our safety work. You will also represent the company's topline safety metric as well as prioritize incoming requests from partner teams to expand our safety measurement platform to more use cases. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Partner closely with data science, research, engineering, policy teams, and other stakeholders to craft a vision for understanding safety outcomes and prevalence on our platforms. Define strategic priorities and product roadmaps focused on improving safety measurement approaches will scaling our measurement platform to more use cases, products, and cross-functional team needs. Establish repeatable processes to integrate cutting-edge AI safety research into OpenAI’s safety m

VTS's Lease integrations connect our platform to the property management and accounting systems - Yardi, MRI, JDE, and others - that our customers run their portfolios on. When those integrations are healthy, data flows automatically and customers trust what they see in VTS. The Integrations and API Support Advisor owns the health of these integrations end-to-end - proactively monitoring for failures before customers notice them, and resolving the inbound requests that come in when something breaks or needs to change. Success in this role is simple to state and hard to deliver: every integration stays active, and customers can always rely on the integrity of the data VTS is showing them. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office 4 days a week. ** What you can expect as an Integrations and API Support Advisor: At VTS, you'll join the Integrations Support team as a critical layer between our customers' source systems and the VTS platform. You'll: Own Integration Health : Monitor active Yardi, MRI, SAP, and custom API integrations for failures, stalled syncs, and missed feeds. Proactively identify and resolve issues - such as failed nightly imports, integrations stuck in "processing," or ETL files not arriving via SFTP - before they escalate into customer-reported problems. Resolve Data Integrity Issues : Investigate and fix discrepancies between VTS and source systems, including mismatched square footage, missing or duplicated leases, orphaned records, incorrect rent or lease terms, and unit/space mapping errors. Trace root causes across the integration pipeline rather than just patching symptoms. Manage the Customer Support Queue : Respond to and resolve inbound tickets covering the full integration lifecycle - API credential and access requests, asset archiving and disposition processing, source ID/BU remapping, stacking and site plan corrections, and MRI/Yardi version upgrades and migrations. Par

Role Purpose: At Jumio, you will work for one of the market leaders in the global identity verification space that is helping to make the digital world a safer place for everyone. As a Software Development Engineer in the MLOpsTeam, you will develop the blueprint for highly scalable and performant ML model serving. Role Value: As a Software Engineer (SDE III), you will drive the continuous improvement of the infrastructure and applications to manage the lifecycle of ML assets (data, models) to better developer experience and strengthen governance capabilities. Secondly, you will design and implement robust ML infrastructure for model deployment, serving, and optimization. You will work on efficient CI/CD pipelines for ML models and leverage advanced compilers or hardware optimization to maximize inference performance while optimizing costs. We welcome you to challenge us to impact our software development processes and tools. Example Responsibilities: Upgrade ML assets (models, data) management systems for better developer experience and robust governance capabilities Build and optimize model serving infrastructure with a focus on inference latency and cost optimization Architect efficient inference pipelines that balance latency, throughput, and cost across various acceleration options Implement cost-efficient, enterprise-scale solutions Collaborate in a cross-functional, distributed team for continuous system improvement Work with MLEs, QA Engineers, and DevOps Engineers Evaluate and implement new technologies and tools Contribute to architectural decisions for distributed ML systems Experience and Qualifications : 5+ years of experience in software engineering with Python Experience with model lifecycle management (MLFlow, Weights & Biases or equivalent) Experience with data management ecosystem (quality, transformation, catalog) Experience with ML frameworks, particularly PyTorch Experience optimizing ML models with hardwar

The Head of Contract Administration is a central figure in managing the full lifecycle of government contracts for coal mining projects. This role involves direct interfacing with Mine Owner PSUs of MDO contracts, ensuring strict adherence to contractual terms and conditions, and managing the administration and compliance aspects from contract signing to project closure. The incumbent is responsible for mitigating risks associated with commercial agreements, maintaining continuous correspondence with stakeholders, and ensuring the organization's interests are safeguarded. He oversees the entire scope of Contract Administration including assessing risks and opportunities and formulating strategy for the same. Source: Adani Group | Job ID: 51515

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 Stripe processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure. What you’ll do You will work closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end-to-end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company. Responsibilities Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions. Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems. Working directly with product teams and ML engineers to improve their day-to-day pr